{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "36c5967d-20e3-4933-b218-e94e1a1786fc",
   "metadata": {},
   "source": [
    "# 崩坏3.0视频数据分析"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "80b26432-d149-438b-9700-350fa51081f2",
   "metadata": {},
   "source": [
    "## 一. 数据导入"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "5b249feb-7e7c-47a6-99b8-9b8db5957624",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "原始数据形状: (1000, 5)\n",
      "\n",
      "前5行数据:\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>title</th>\n",
       "      <th>play</th>\n",
       "      <th>duration</th>\n",
       "      <th>up主</th>\n",
       "      <th>bvid</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>【崩坏3】主线第一部全剧情合集（不含战斗）</td>\n",
       "      <td>2593192</td>\n",
       "      <td>5774:16</td>\n",
       "      <td>千万-伏特</td>\n",
       "      <td>BV1LV411Z7fz</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>《崩坏3》动画短片「因你而在的故事」</td>\n",
       "      <td>22052766</td>\n",
       "      <td>8:26</td>\n",
       "      <td>崩坏3第一偶像爱酱</td>\n",
       "      <td>BV1fY4y1F7GL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>《崩坏3》动画短片「薪炎永燃」</td>\n",
       "      <td>24374494</td>\n",
       "      <td>7:56</td>\n",
       "      <td>崩坏3第一偶像爱酱</td>\n",
       "      <td>BV1b44y1q7Cb</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>【崩坏3】8.3版本萌新入坑/回坑玩家保姆扫盲级喂饭攻略</td>\n",
       "      <td>22720</td>\n",
       "      <td>78:6</td>\n",
       "      <td>依辰mm</td>\n",
       "      <td>BV1Sy76zxE5X</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>《崩坏3》英文歌保姆级教唱</td>\n",
       "      <td>1043</td>\n",
       "      <td>NaN</td>\n",
       "      <td>繁星Cong2</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          title      play duration        up主          bvid\n",
       "0         【崩坏3】主线第一部全剧情合集（不含战斗）   2593192  5774:16      千万-伏特  BV1LV411Z7fz\n",
       "1            《崩坏3》动画短片「因你而在的故事」  22052766     8:26  崩坏3第一偶像爱酱  BV1fY4y1F7GL\n",
       "2               《崩坏3》动画短片「薪炎永燃」  24374494     7:56  崩坏3第一偶像爱酱  BV1b44y1q7Cb\n",
       "3  【崩坏3】8.3版本萌新入坑/回坑玩家保姆扫盲级喂饭攻略     22720     78:6       依辰mm  BV1Sy76zxE5X\n",
       "4                 《崩坏3》英文歌保姆级教唱      1043      NaN    繁星Cong2           NaN"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from datetime import datetime\n",
    "import jieba\n",
    "import re\n",
    "from sklearn.feature_extraction.text import TfidfVectorizer\n",
    "from sklearn.decomposition import LatentDirichletAllocation\n",
    "from sklearn.ensemble import RandomForestRegressor, RandomForestClassifier\n",
    "from sklearn.model_selection import train_test_split, GridSearchCV\n",
    "from sklearn.metrics import mean_squared_error, classification_report, confusion_matrix\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.cluster import KMeans\n",
    "from wordcloud import WordCloud\n",
    "from collections import Counter\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "# 1. 数据导入与初步探索\n",
    "df = pd.read_csv('bilibili_videos.csv')\n",
    "print(\"原始数据形状:\", df.shape)\n",
    "print(\"\\n前5行数据:\")\n",
    "display(df.head())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "960a4545-0d54-40f8-9369-132c87824d6e",
   "metadata": {},
   "source": [
    "## 二. 数据清洗"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "669791b0-297a-4a91-af51-4a403e1704ad",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "清洗后数据统计:\n",
      "               play  duration_min\n",
      "count  1.000000e+03    999.000000\n",
      "mean   7.935349e+05     61.162679\n",
      "std    2.425015e+06    502.830793\n",
      "min    0.000000e+00      0.083333\n",
      "25%    1.739175e+04      1.483333\n",
      "50%    1.141965e+05      3.416667\n",
      "75%    5.149982e+05     10.000000\n",
      "max    3.029965e+07  10429.683333\n"
     ]
    }
   ],
   "source": [
    "# 处理播放量\n",
    "df['play'] = pd.to_numeric(df['play'], errors='coerce')\n",
    "\n",
    "# 时长转换函数\n",
    "def convert_duration(dur):\n",
    "    try:\n",
    "        if pd.isna(dur):\n",
    "            return np.nan\n",
    "        if ':' in str(dur):\n",
    "            parts = str(dur).split(':')\n",
    "            if len(parts) == 2:  # 分钟:秒\n",
    "                return int(parts[0]) + int(parts[1])/60\n",
    "            elif len(parts) == 3:  # 小时:分钟:秒\n",
    "                return int(parts[0])*60 + int(parts[1]) + int(parts[2])/60\n",
    "        return float(dur) if str(dur).replace('.','').isdigit() else np.nan\n",
    "    except:\n",
    "        return np.nan\n",
    "\n",
    "df['duration_min'] = df['duration'].apply(convert_duration)\n",
    "\n",
    "# 清洗后的数据\n",
    "print(\"\\n清洗后数据统计:\")\n",
    "print(df[['play', 'duration_min']].describe())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "98d17d4a-f6f5-48a7-820c-8f7f5bb91d2e",
   "metadata": {},
   "source": [
    "## 三. 特征工程"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9299bca3-2841-42d7-af3e-d88d587b4b3c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 3.1 基础特征\n",
    "df['title_length'] = df['title'].str.len()\n",
    "df['has_special_chars'] = df['title'].apply(lambda x: bool(re.search(r'[【】《》「」]', str(x))))\n",
    "\n",
    "# 3.2 文本特征\n",
    "# 中文分词函数\n",
    "def chinese_word_cut(text):\n",
    "    text = str(text)\n",
    "    # 去除特殊符号\n",
    "    text = re.sub(r'[【】《》「」\\-\\|\\.\\!\\/_,$%^*()+\\\"\\']+|[+——！，。？、~@#￥%……&*（）]+', '', text)\n",
    "    return \" \".join(jieba.cut(text))\n",
    "\n",
    "df['title_cut'] = df['title'].apply(chinese_word_cut)\n",
    "\n",
    "# TF-IDF特征\n",
    "tfidf = TfidfVectorizer(max_features=50, stop_words=['崩坏', '视频'])\n",
    "title_tfidf = tfidf.fit_transform(df['title_cut'])\n",
    "tfidf_features = pd.DataFrame(title_tfidf.toarray(), columns=[f\"tfidf_{i}\" for i in tfidf.get_feature_names_out()])\n",
    "\n",
    "# 3.3 UP主相关特征\n",
    "up_stats = df.groupby('up主').agg(\n",
    "    up_avg_play=('play', 'mean'),\n",
    "    up_video_count=('bvid', 'count')\n",
    ").reset_index()\n",
    "\n",
    "df = df.merge(up_stats, on='up主', how='left')\n",
    "\n",
    "# 3.4 目标变量\n",
    "df['is_popular'] = (df['play'] > df['play'].quantile(0.75)).astype(int)  # 前25%定义为热门\n",
    "\n",
    "# 合并所有特征\n",
    "features = pd.concat([\n",
    "    df[['duration_min', 'title_length', 'has_special_chars', 'up_avg_play', 'up_video_count']],\n",
    "    tfidf_features\n",
    "], axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2579c1ca-6b36-460d-aa10-f326900d6599",
   "metadata": {},
   "source": [
    "## 四. 探索性分析(EDA)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "c5447005-d88b-4a6a-8cf7-82905b425f71",
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1500x1200 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15, 12))\n",
    "\n",
    "# 4.1 播放量分布\n",
    "plt.subplot(2, 2, 1)\n",
    "sns.histplot(df['play'].dropna(), bins=50, kde=True)\n",
    "plt.title('播放量分布')\n",
    "plt.xlabel('播放量')\n",
    "\n",
    "# 4.2 视频类型分析\n",
    "df['video_type'] = df['title'].apply(lambda x: '攻略' if '攻略' in str(x) else \n",
    "                                    '剧情' if '剧情' in str(x) else\n",
    "                                    '动画' if '动画' in str(x) else '其他')\n",
    "\n",
    "plt.subplot(2, 2, 2)\n",
    "df['video_type'].value_counts().plot.pie(autopct='%1.1f%%')\n",
    "plt.title('视频类型分布')\n",
    "\n",
    "# 4.3 时长与播放量关系\n",
    "plt.subplot(2, 2, 3)\n",
    "sns.scatterplot(x='duration_min', y='play', data=df, alpha=0.6)\n",
    "plt.title('时长与播放量关系')\n",
    "\n",
    "# 4.4 UP主分析\n",
    "plt.subplot(2, 2, 4)\n",
    "df['up主'].value_counts().head(10).plot.barh()\n",
    "plt.title('发布视频最多的UP主')\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bd454fe0-0eb5-4440-9aa3-31a2aa06fdc7",
   "metadata": {},
   "source": [
    "## 五. 建立模型"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "df7aa503-8cc9-4a34-b41e-606ec27665db",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "分类模型评估报告:\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.96      1.00      0.98       147\n",
      "           1       1.00      0.89      0.94        53\n",
      "\n",
      "    accuracy                           0.97       200\n",
      "   macro avg       0.98      0.94      0.96       200\n",
      "weighted avg       0.97      0.97      0.97       200\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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T+C0BwLmJsAkAQDVuvfVWffnllzp8+HC1YdPhcMjhcCg9PV0HDx5UZmamSkpKjPc2SlJaWpqSk5PlcDhUXFyspk2bKjQ0VFlZWeratavS09NdNpyp7D2bTqdTRUVFSk9PP2lm0sfHR3369FHjxo2VnZ2tb7/9VlFRUWrTpo0ee+wxjR8/Xn379tWwYcM0ZMiQk5b/ls+gSseX9R4+fFg+Pj4udR07dkzZ2dkqLS1VQUGBWrVqJS8vL5dx/P399fLLL2v06NHasGGDyyZCDz/8sPbu3avBgwerrKzM2LXXZDJp+fLlmjx5ssaNGydJuuWWW/Tyyy+7jP3EE0/o448/1uOPP66LL75Yn332WaU79P7VunXr9Oeff+rPP//U5Zdf7tJX/gqWjh07asuWLXr00Uf1+++/Kz4+XlOmTDHO+89//qPly5fr559/rtE9AaChMTmrejACAIAG5s8//1SrVq30+++/uwQ7Sfrjjz/04YcfatmyZbLZbMYGPieKj4/Xv//9bz344IN64okn5OnpWelOpSUlJSoqKtKdd96pN954QxMnTtTcuXNltVpPel1IZUpKStS+fXv98MMPKi0t1V133aXffvtN+fn5SklJkYeHh2688Ubde++9RqhyOp3673//q3feeUcLFy6Ur6+vfvrpJwUHBxvjzps3T48//rgyMjK0du1a9e3bt9pafv75Z5fXppzo0UcfVXp6uhISEmr0vapjMpm0ZMkSDR8+3C3j1VZOTo46deqkpKSkk95/CgA4jrAJAMAJ9u/fr5CQEO3evVsdO3Z06SsuLlbr1q0VERGhF1980WW31HJPPfWUXn31VR0+fPjvKtnFF198obVr16p9+/bq3r27LrroopNmG0+Uk5OjP/74Q927d3dpf/PNNzV9+nRlZWXJ4XCosLBQVqtVFsvJi6LK+318fCrdoMfpdCo7O7vKHXFro77DpnR8Ka47NoQCgHMVYRMAgFqoy46nAAA0RIRNAAAAAIDb8adZAAAAAIDbETYBAAAAAG5H2AQAAAAAuB1hEwAAAADgdifvXw78RVlZmdLT09WkSROZTKb6LgcAAABAPXE6ncrLy1ObNm2q3Z2dsIlqpaenu7zoGwAAAEDDtn//fgUFBVV5DmET1WrSpImk4/9B+fn51XM1AAAAAOpLbm6ugoODjYxQFcImqlW+dNbPz4+wCQAAAKBGj9exQRAAAAAAwO0ImwAAAAAAtyNsAgAAAADcjrAJAAAAAHA7wiYAAAAAwO3YjRY11nXGSpmtvvVdBgAAANBgpMYPqO8S6oyZTQAAAACA2xE2AQAAAABuR9g8C61du1ahoaH1XQYAAAAAVIqwCQAAAABwO8ImAAAAAMDtzrmwWdESU5PJpISEBPXo0UM33nij/P39FRUVpYyMjBqNuWHDBl100UXy9fVVjx49tGvXLknSwoUL1adPH+O87OxseXt769ChQ5KkHTt2qGvXrmrWrJkeeOABdezYUa+99lqV94qNjVX//v119dVXy9/fX7feeqtyc3NrVOeyZcvUoUMHNWrUSNdee63S09MlSU899ZQGDPi/Xaz27t0rb29v5eTk1GhcAAAAAKitcy5sVmXLli264oortG3bNlmtVsXExFR7TVlZmYYPH66hQ4fq999/11VXXaUHH3xQkjRw4EBt3bpV2dnZkqSvv/5avXr1UsuWLSVJMTExGjlypL755hu98847euedd3T77bdXe88VK1borrvu0g8//KDU1FQ9/vjj1V5jt9s1YsQITZs2TXv37lVAQICefvppSdItt9yi1atXG6H1P//5j2644Qb5+/tXOFZRUZFyc3NdPgAAAABQGw0qbAYFBWnq1KkKCwtTbGysPv/8c5WWllZ73datW/Xwww9r//79ys7O1q+//ipJ8vPzU9++ffX1119LOh4Shw0bZly3bds23XzzzbrgggvUpUsXpaWlqWnTptXer3fv3rrjjjvUvn17TZ06VcuWLav2msaNG+uPP/7QrbfeqpSUFB07dsyos0OHDurYsaOSkpIkSZ9++qlGjBhR6VgzZ86Uv7+/8QkODq72/gAAAABwonM+bObn5xs/BwUFyWQySZLatm0rh8OhrKysKq83m82aNWuW2rZtq3vvvVd2u10Oh8PoHz58uL788ktJx2c2hw4davRFRETo+++/15EjR7Rnzx517ty5RjWfGO7atm2rzMzMaq9xOp165JFH1LZtWz3yyCMqKSlxqfOWW27RJ598oszMTG3fvl2DBw+udKxp06YpJyfH+Ozfv79GdQMAAABAuXMubJpMJpWVlRnHP/74o/FzWlqanE6nJGn//v2yWCxq0aJFleOtXbtW8+bN065du7R582bdddddLv2DBw/W6tWr9fPPPyskJESBgYGSjoe/zp07a+LEiWrdurXuuOMOXXDBBTX6DqmpqcbP+/fvV+vWrau9ZuHChdq0aZP++OMPrV+/XoMGDXLpHzFihFasWKFFixYpKipKjRs3rnQsq9UqPz8/lw8AAAAA1MY5Fzbbtm2rjIwM/fHHH8rPz9eMGTOMvvT0dM2cOVP79u1TXFycbrzxRnl4eFQ5Xl5enqTjm/9s2LBBkydPNgKrJDVr1kwdO3bUzJkzNXz4cKP9119/1XfffacNGzYoJSVFL7/8co2/w6ZNm5SYmKg9e/boueeec1maW1WdTqdTR44c0ZdffqmnnnrKpc7w8HB16NBBsbGxVS6hBQAAAAB3OOfCZkREhO6//3717t1bffr00f3332/09ezZU5s3b1bXrl1VXFys119/vdrxoqKiFBUVpYsvvlgxMTEaN26c0tPTXZa2Dhs2TIsWLXJZQnv++ecrICBAV199tcLCwuTj41OjDYkkadCgQZo3b54uvvhihYeHuwTmyvzzn/9UaGioOnXqpLi4OI0fP167d+9WYWGhcc6IESNUWlrqsjMtAAAAAJwOJueJ01/nsISEBCUkJGjt2rV/y/3eeecdffTRR5o3b558fX21Y8cO/eMf/1BmZmaVy1JjY2OVmpqqhIQEt9azd+9eLVq0SMnJyVqwYEGtrs3NzT2+UdCkj2S2+rq1LgAAAACVS40/syaKyrNBTk5OtY/bWf6mms5oNputwvbOnTtr48aNdRqzb9++Wrhwobp27aqCggK1a9dO8fHxys7OVkhISIXXREVFqWPHjnW6X3UuvPBCBQQEGDvSAgAAAMDp1GBmNqty4oY8J/Ly8lKbNm3ceq/S0lIdOHCgwj5fX18FBAS49X7uUJu/XgAAAAA4dzGzWUuhoaF/270sFsvfej8AAAAAqA/n3AZBAAAAAID6R9gEAAAAALgdYRMAAAAA4HaETQAAAACA2xE2AQAAAABuR9gEAAAAALgdYRMAAAAA4HaETQAAAACA2xE2AQAAAABuR9gEAAAAALgdYRMAAAAA4HaETQAAAACA2xE2AQAAAABuR9gEAAAAALidpb4LwNmj64yVMlt967sMVCE1fkB9lwAAAABIYmYTAAAAAHAaEDYBAAAAAG7X4MJmamqqTCbTKZ8DAAAAAKhcgwubISEhstvt9V1GvQgNDdXatWvruwwAAAAADUCDC5tms1k2m62+ywAAAACAc1q9hs21a9cqNDTUpc1kMikhIUE9evTQjTfeKH9/f0VFRSkjI6Pa8RYuXKg+ffoYx9nZ2fL29tahQ4eMtsqWyCYlJSkiIkItWrTQ+++/79K3ZcsWXX755fL399fQoUOVk5Nj9H377be68MIL1bRpU40aNUrZ2dk1+u6rV69W9+7d1aRJE/Xv318HDhyodsyEhARFRkZW+F3K+95++221atVKrVq10ieffCJJioqKkslk0h9//KG+ffvKZDIpPj6+0tqKioqUm5vr8gEAAACA2jhjZza3bNmiK664Qtu2bZPValVMTEy11wwcOFBbt241wtnXX3+tXr16qWXLllVel5mZqREjRmjq1KnatGmTkpKSjL7s7Gz1799f/fv3144dO5Sbm6spU6ZIkvbv369//OMfuvfee/Xjjz/q6NGjio6OrrbOffv2adCgQZo0aZJ27dolPz8/3Xfffac0piTt3LlTn3zyiTZs2KAxY8Zo0qRJkqSlS5fKbrcrODhYn332mex2ux544IFKx5k5c6b8/f2NT3BwcI3uDwAAAADlztj3bAYFBWnq1KkymUyKjY3VZZddptLSUlkslZfs5+envn376uuvv9bNN9+sFStWaNiwYdXea8WKFQoLC9O4ceMkSbGxsRow4Pj7Cj///HN5enpqxowZMplMevDBB3XHHXdIkubPn69evXoZ17355psKCgrSwYMH1bp160rvt2jRIl155ZW68847JUkvvfSStm3bVu2Y1Tl27JgSExMVEBCgO++8U88995wkqVGjRpKOLyFu3LhxtcuIp02bpsmTJxvHubm5BE4AAAAAtXJGhc38/Hzj56CgIGOJaNu2beVwOJSVlaVWrVpVOcbw4cP15Zdf6uabb9bXX3+tp59+utr7ZmRkKCQkxDgODw83fj5w4IAOHTqkpk2bSpLKysqUl5enwsJC7d+/X+edd55xbtu2bWW1WpWWllZl2PzrdUFBQQoKCqqw78Qx/+rE35ckderUSQEBAZIkLy+var93ZaxWq6xWa52vBwAAAIB6XUZrMplUVlZmHP/444/Gz2lpaXI6nZKOBzCLxaIWLVpUO+bgwYO1evVq/fzzzwoJCVFgYGC11wQEBCg9Pd3l3uWCgoJ0ySWXaNu2bdq2bZu2b9+urVu3ytPTUyEhIfr999+Nc9PT01VUVKR27dpVeb/g4GClpqYax7/99psuuugilZWVVTlmVb8v6fjMblXMZrPxOwUAAACA06lew2bbtm2VkZGhP/74Q/n5+ZoxY4bRl56erpkzZ2rfvn2Ki4vTjTfeKA8Pj2rHbNasmTp27KiZM2dq+PDhNaqjX79+Sk5OVmJiolJSUhQbG2v0DRgwQGlpadq8ebN8fHz08ccfKyoqSk6nU7fddps2btyot99+W/v27dO//vUv3XTTTdXOvo4cOVLffvutEhIStH//fj399NMKCAiQ2Wyucsy2bdtq165dys3N1aFDh/T888/X6PuVCw8P11dffaWMjAytXr26VtcCAAAAQG3Ua9iMiIjQ/fffr969e6tPnz66//77jb6ePXtq8+bN6tq1q4qLi/X666/XeNxhw4Zp0aJFGjp0aI3ODwoK0oIFCxQXF6c+ffqod+/eRp/NZtPy5cv10ksv6bzzztOSJUu0fPlyWSwWBQcH6/PPP9fs2bN10UUXydfXV++991619wsLC9OyZcv08ssvq0uXLsrOzjauq2rMa665Rv369VO3bt00YMAAPfroozX+nUjSCy+8oM8//1whISEugRoAAAAA3M3kPAPXVSYkJCghIUFr166t71Kg4xsE+fv7K3jSRzJbfeu7HFQhNX5AfZcAAACAc1h5NsjJyan2Mb4zaoOgmqhsJ9XOnTtr48aNf28xlUhLS1P37t0r7IuKitLixYv/5ooAAAAA4O91Rs5sVuXEjXVO5OXlpTZt2vy9xVSitLRUBw4cqLDP19fX2DH2bFGbv14AAAAAOHed0zOboaGh9V1CtSwWy1lRJwAAAACcLvW6QRAAAAAA4NxE2AQAAAAAuB1hEwAAAADgdoRNAAAAAIDbETYBAAAAAG5H2AQAAAAAuB1hEwAAAADgdoRNAAAAAIDbETYBAAAAAG5H2AQAAAAAuB1hEwAAAADgdoRNAAAAAIDbETYBAAAAAG5H2AQAAAAAuJ2lvgvA2aPrjJUyW33ruwycIDV+QH2XAAAAAFSImU0AAAAAgNudE2EzNTVVJpOpwd7/RGdSLQAAAAAarnMibP4dIiMjlZCQUGFfSEiI7Hb731tQJc6kWgAAAAA0XIRNNzCbzbLZbPVdhqQzqxYAAAAADddZGzaTkpIUERGhFi1a6P3335ckrV27VqGhoS7nmUwmpaamSpKio6MVGxur+fPnq0OHDnrzzTeN8zZs2KCLLrpIvr6+6tGjh3bt2iVJiomJkclk0rp16zRmzBiZTCbFxMS43KOypas7d+5Unz595O/vr3/84x86cOCAS53Lly9Xu3bt1KxZM73++uvVfufIyEiNGTNGLVu21KhRozRmzBg1adJEy5cvr7KWut4PAAAAAOrqrAybmZmZGjFihKZOnapNmzYpKSmpxteuXLlSr7/+ul588UUNHjxYklRWVqbhw4dr6NCh+v3333XVVVfpwQcflCTNmjVLdrtdvXv31uzZs2W32zVr1qxq73P06FH169dP119/vXbs2KHg4GDdeOONKisrkyRlZWXpueee0xdffKEnn3xSU6ZMUWFhYbXj7tu3TwkJCVq0aJEuueQSDR8+XJ999lm119XmfkVFRcrNzXX5AAAAAEBtnJWvPlmxYoXCwsI0btw4SVJsbKwGDKjZKyBSUlK0Z88e+fv7u7Rv3bpVTZs21Y4dO5Sdna1ff/1VkuTj4yMfHx9ZLBb5+vrWeInqZ599piZNmmjGjBmSpFdffVUtW7bU5s2bJR0Po2+++aa6dOmi9u3ba8KECcrMzFS7du2qHPfWW29Vly5dJEljx47V4cOHjZnbqtTmfjNnzlRcXFyNvicAAAAAVOSsnNnMyMhQSEiIcRweHl7hefn5+Se1/fOf/zwpaJrNZs2aNUtt27bVvffeK7vdLofDcUo17t+/X2FhYcaxt7e32rZtq7S0NElS06ZN1b17d0mSl5eXJMnpdFY7rre3d4U/V6c295s2bZpycnKMz/79+2t8HwAAAACQztKZzYCAAKWnpxvH5QHOZDIZy1Ql6ccffzzp2kaNGp3UtnbtWs2bN0+7d+9WQECAvvjii5OuNZvNNQqD5UJCQrRv3z7juKioSOnp6WrXrp0KCgrk5+dX47HcoTb3s1qtslqtp7EaAAAAAOe6s3Jms1+/fkpOTlZiYqJSUlIUGxsrSWrbtq0yMjL0xx9/KD8/31jCWp28vDxJUnZ2tjZs2KDJkyefFCzDw8O1Zs0aZWRkaNWqVdXOfA4cOFB5eXmKi4vTH3/8oYkTJ6p9+/a67LLLav+FAQAAAOAsc1aGzaCgIC1YsEBxcXHq06ePevfuLUmKiIjQ/fffr969e6tPnz66//77azReVFSUoqKidPHFFysmJkbjxo1Tenq6MjMzjXOmT5+ulJQUtWvXTjExMS4zqBVp3LixVq5cqa+++krdunVTWlqali1bJrP5rPyVAwAAAECtmJy1WRuKBik3N1f+/v4KnvSRzFbf+i4HJ0iNr9nGWAAAAIA7lGeDnJycah/VOyuf2TyXVbbbbefOnbVx48a/txgAAAAAqCPC5hlm27ZtFbaX7yALAAAAAGcDltGiWrWZKgcAAABw7qpNNmC3GgAAAACA2xE2AQAAAABuR9gEAAAAALgdYRMAAAAA4HaETQAAAACA2xE2AQAAAABuR9gEAAAAALgdYRMAAAAA4HaETQAAAACA2xE2AQAAAABuR9gEAAAAALgdYRMAAAAA4HaETQAAAACA2xE2AQAAAABuZ6nvAnD26DpjpcxW3/ouo16lxg+o7xIAAACAswIzmwAAAAAAtyNsAgAAAADc7pwMm6mpqTKZTH/bdVVZu3atQkND3TpmbUVHRys2NrZeawAAAADQsJzVYTMyMlIJCQkntYeEhMhut9fqmnPB6QjLAAAAAFAXZ3XYrIzZbJbNZqvvMgAAAACgwTorw2ZMTIxMJpPWrVunMWPGyGQyKSYmxuivaIavumuqsmXLFl1++eXy9/fX0KFDlZOTc8rfYcWKFerWrZtsNpvGjh2roqIiSVJsbKyio6P15JNPymazKSwsTBs2bDCuW7RokVq3bq3zzjtPDz74oAICArR9+3Z5e3srLCxMkmQymWQymbRp0ybjOofDoXvvvVeNGzdW165d9euvv57ydwAAAACAypyVYXPWrFmy2+3q3bu3Zs+eLbvdrlmzZrn9GknKzs5W//791b9/f+3YsUO5ubmaMmXKKdW/d+9e3Xjjjbr//vu1ZcsWbd68WS+88ILR/8UXX+j333/X1q1b1bt3b02bNk2SZLfbdffdd2vhwoWKjY3VggULtG3bNnXo0EGZmZnavn27cZ7dbtdll11mjDlnzhz5+flp586dCggI0DPPPFNpfUVFRcrNzXX5AAAAAEBtnJVh08fHRzabTRaLRb6+vrLZbPLx8XH7NZL0+eefy9PTUzNmzFC7du304IMPavny5adU/4cffqgLL7xQY8eOVfv27XXPPfe4jGmxWDRnzhyFhYXpjjvu0P79+yVJe/bsUZMmTXTNNddoxIgROnjwoEwmk7y9veXv7y8/Pz9Jks1mk81mk4eHhzFmcHCwZs6cqdDQUN16663GmBWZOXOm/P39jU9wcPApfV8AAAAADY+lvgs40x04cECHDh1S06ZNJUllZWXKy8tTYWGhvL296zzm1q1bjedKS0tL1bhxY6O/Z8+eslqtkiQvLy85nU5JUmhoqOx2u1JSUnTgwAE1a9ZMrVq1qtE9r776auPnE8esyLRp0zR58mTjODc3l8AJAAAAoFbO6rBpNpurDE3uuCYoKEiXXHKJPvzwQ0mS0+lUTk6OPD09a3Xfv445aNAgvfTSS5KOP0+Zn59v9JfPUP6Vl5eXOnbsqC5dusjDw0PvvfeezOb/m5wu/9npdJ70zGplY1bEarUaYRcAAAAA6uKsXEZbLjw8XGvWrFFGRoZWrVolh8Ph9msGDBigtLQ0bd68WT4+Pvr4448VFRVV65B7oltvvVXfffed9uzZI6vVqtdee01jxoyp9rrFixerbdu22rp1qw4cOKBbbrnFpT8wMFC+vr5KSkrSH3/84bJBEAAAAAD8nc7qsDl9+nSlpKSoXbt2iomJUVlZmduvsdlsWr58uV566SWdd955WrJkiZYvXy6Lpe6TwuHh4Xr//fc1efJkRUREaMeOHVq0aFG11/3jH//Qhg0b1KtXLzVv3lwtW7bUvHnzjH5PT0/NnTtX48ePV4cOHbRs2bI61wgAAAAAp8LkPJUpOvytRo8erXbt2mnChAkymUyaP3++FixYoB9//PG03jc3N/f4RkGTPpLZ6nta73WmS40fUN8lAAAAAPWmPBvk5ORU+6jeWT2zWZ/S0tKMXV//+rn11ltPyz1vu+02ffbZZwoLC1NoaKgWLVqk559//rTcCwAAAABOxVm9QVB9atOmjbZt21Zhn6/v6Zn9i4qKUlRU1GkZGwAAAADciWW0qFZtpsoBAAAAnLtYRgsAAAAAqFeETQAAAACA2xE2AQAAAABuR9gEAAAAALgdYRMAAAAA4HaETQAAAACA2xE2AQAAAABuR9gEAAAAALgdYRMAAAAA4HaETQAAAACA2xE2AQAAAABuR9gEAAAAALgdYRMAAAAA4HaETQAAAACA21nquwCcPbrOWCmz1fe03iM1fsBpHR8AAADA34OZTQAAAACA2xE2AQAAAABuV6uwuXbtWoWGhp6mUs4MsbGxio6O/tuuq0h0dLRiY2PdMhYAAAAA1Aee2fyLRx55RGVlZfVdBgAAAACc1Qibf+Ht7V3fJQAAAADAWa9Oz2wuX75c7dq1U7NmzfT6669LkjZs2KCLLrpIvr6+6tGjh3bt2mWcv2rVKnXu3Fm+vr7q1auX9u7dW6P7LFq0SGFhYWrUqJFuuOEGHT58WNLxZaa33nqrLrnkEjVr1kz33nuvSkpKjOvef/99tW/fXi1atNCjjz4qp9Np9L3yyisKCQlR8+bN9a9//cvlOqny5bBPPfWUWrVqpaZNm2rs2LFyOBw1/n1VpqpaHA6H7r33XjVu3Fhdu3bVr7/+WqNaTCaTfvnlF40fP17NmjXTsWPHJElOp1MPP/ywWrZsqaZNm+q+++5z+b0AAAAAgDvVOmxmZWXpueee0xdffKEnn3xSU6ZMUX5+voYPH66hQ4fq999/11VXXaUHH3zQuOb222/XmDFj9Ouvv6pz5856/PHHq71PXl6e/vnPf2rmzJn65ZdfZLFY9NJLLxn9y5cv19NPP621a9dq5cqVRuj99ttvNXbsWL388stavXq1EhMTtWDBAknHw+vMmTM1f/58bdiwQWvXrtXs2bOrreWLL77Q888/ry+++EI//PCD1q9fr6VLl9b2V+eiulrmzJkjPz8/7dy5UwEBAXrmmWdqXMu4cePUqFEjLV261JipXblypd5++22tWrVK3377rZYtW6avvvqqwtqKioqUm5vr8gEAAACA2qj1MtqjR4/qzTffVJcuXdS+fXtNmDBBhw4d0tatW9W0aVPt2LFD2dnZLjNxPj4+KikpUbNmzTR37lyVlpZWX5jFIovFouLiYgUGBmr58uUuz1IOHTpU/fv3lyTde++9WrZsmR544AF98MEHGjJkiAYNGiRJGj16tJYvX67bb79d7733niZNmqSrrrpKkrRgwYIa1XL11VcrLS1NTqdTGzdulCSX71cX1dUSHBysmTNnSpJuvfVWLVq0qMa1dOvWTS+//LJLm4+PjySppKREF198sX7//XeZzRX/rWHmzJmKi4s7pe8HAAAAoGGr9cxm06ZN1b17d0mSl5eXpONLNGfNmqW2bdvq3nvvld1ud1naOX/+fH3zzTdq27at+vbtq507d1Z7Hx8fHy1evFhz585VQECABg8erP379xv9wcHBxs9t27ZVZmamJOnAgQNatmyZbDabbDab/v3vfystLU2StH//fp133nnGdRdffLF69OhRbS2HDx/W0KFD1alTJ7355pvy9vY+5WW01dVy9dVXGz97eXkZS15rUsvEiRNPut/VV1+thx9+WGPGjFFAQIAmTpyooqKiCmubNm2acnJyjM+Jv3cAAAAAqIlah00/P7+T2tauXat58+Zp165d2rx5s+666y6jLz8/X6Wlpfr66691+PBh9enTp0avCDly5IhatWql9evXKzMzUy1atNCkSZOM/tTUVOPn/fv3q3Xr1pKkoKAgjR8/Xtu2bdO2bdu0fft2JSYmSjoeUE+8bsGCBRo7dmy1tcyYMUPBwcE6ePCgPv/8c51//vnVXlOd6mqp6Pdc01oaNWp0Utvvv/+uoUOH6ueff9bOnTu1YcMGvfXWWxXew2q1ys/Pz+UDAAAAALVRpw2C/iovL0+SlJ2drQ0bNmjy5MnGTFxpaaluuOEGLViwQH/++aecTmeNlq7++eefioyM1IoVK3TkyBFjrHKffvqpvvjiC+3YsUOzZ8/WsGHDJEl33HGHli1bpoMHD8piseixxx7TY489Jkm688479corr2j9+vVKTk7WCy+8oPDw8Bp9P4fDoYMHD+r111/XJ598csqb6/zdtaxatUpDhgzR1q1bVVBQIEk1+ncAAAAAgLpwy6tPoqKitGnTJl188cUKCwvTuHHj9MgjjygzM1OtWrXS/Pnz9fjjj2vs2LGKiIiodEbtRB07dtRLL72kf/3rXzp48KAuuOACvfPOO0b/zTffrKlTp2r//v0aPXq0xo8fL0m68sorFRcXp9GjR+vgwYO69tprNXfuXEnHn33MyMjQyJEjVVhYqNtuu81lI6PKPP744xo9erQ6duyo66+/Xrfeequ2bt1ax9+W6qWWMWPGaOvWrbrhhhtUUFCgfv366Z577jml7wAAAAAAlTE5z8L3X0RHRys0NFSxsbH1XUqDkJubK39/fwVP+khmq+9pvVdq/IDTOj4AAACAuivPBjk5OdU+bueWZbR1kZaWZmzi89fPrbfeWl9luc3ChQsr/X7lr2kBAAAAgHOVW5bR1kWbNm20bdu2Cvt8fauePUtISHB/QW42ePBg9erVq8K+Zs2a/c3VAAAAAMDf66xcRou/V22mygEAAACcu86KZbQAAAAAgHMXYRMAAAAA4HaETQAAAACA2xE2AQAAAABuR9gEAAAAALgdYRMAAAAA4HaETQAAAACA2xE2AQAAAABuR9gEAAAAALgdYRMAAAAA4HaETQAAAACA2xE2AQAAAABuR9gEAAAAALgdYRMAAAAA4HaW+i4AZ4+uM1bKbPWt07Wp8QPcXA0AAACAMxkzm2c4h8NxStcXFRW5qRIAAAAAqDnC5hnswIEDCgkJ0b59+4y2iIgIffTRRzW6/ptvvlGnTp108ODB01UiAAAAAFSIsHmCvLw8DRw4UL6+vgoICNCWLVuMvtTUVJlMpiqvr+icqsaszty5c3XhhRcqLCzMaLNarbLZbNVeW1ZWpoceekgdO3ZU69ata3xPAAAAAHCHBvnMZmRkpKKjoxUdHe3SnpCQoIyMDKWkpCg7O1vNmjUz+kJCQmS322t9r6rGrEp2drb+/e9/69tvv3VpN5lMMpur/xtBXFyc9u7dq08++USStHXrVl100UW1rh8AAAAA6oKZzRNkZWWpW7duCgwMVKdOndSqVSujz2w212hGsTZjVuXZZ59VTk6OAgMDq3zusqioSGVlZS5tq1at0jPPPKN58+YpJCREmzZt0iWXXKKkpKRa1w8AAAAAddGgwmZMTIxMJpPWrVunMWPGyGQyKSYmRosXL5bJZFJcXJwSExNlMpnUsWNHl2srW0ablJSkiIgItWjRQu+//77RXpMxK7N9+3ZjrMTERHl7e8tischiseiXX37RDTfcYBx7e3tr165dxrU7duzQzTffrMcff1zDhw9XaWmp7r33Xg0aNEgDBw6sy68NAAAAAGqtQYXNWbNmyW63q3fv3po9e7bsdrtmzZqlYcOGyW63a+rUqRo5cqTsdnuNnq3MzMzUiBEjNHXqVG3atMll5rCuYx45ckQ333yzXnjhBUnSnXfeKYfDodLSUpWWlqpLly5auXKlcVzeJkmbNm3StddeqzFjxmjGjBmSpOeff152u10JCQk1/j0VFRUpNzfX5QMAAAAAtdGgwqaPj49sNpssFot8fX1ls9nk4+MjT09P2Ww2eXt7y8vLSzabTU2aNKl2vBUrVigsLEzjxo1TRESEYmNjjb66junn56dp06Zp0KBBko4v363qGU0PDw+ZTCYlJycrMjJS99xzj15++WVJ0saNG/XCCy/ok08+UdOmTZWdnV2jV6nMnDlT/v7+xic4OLjaawAAAADgRA0qbLpbRkaGQkJCjOPw8PBTHtNisWjMmDG1vq5jx476/vvvFRcXJ+n4st8RI0ZowYIFuvDCCyUdn2195plnqh1r2rRpysnJMT779++vdT0AAAAAGrYGuRut2WyW0+k85XECAgKUnp5uHKelpZ3ymKeifLfZ9PR09e/fX/Hx8frHP/5h9D/yyCMaMGCA/vGPf+jSSy+tdByr1Sqr1Xra6wUAAABw7mqQM5vh4eFas2aNMjIytGrVqhotLa1Iv379lJycrMTERKWkpLgso60vO3bs0FVXXaWpU6fqtttukyTl5+crIyNDwcHBuvjiizVmzBiVlpbWc6UAAAAAzmUNMmxOnz5dKSkpateunWJiYk56dUhNBQUFacGCBYqLi1OfPn3Uu3dvt9VYPvP61xnYsrKySmdl//vf/+rSSy9Venq64uLi1Lx5c3l6esrf318XXnihBg0apJKSEqWkpOjVV191W60AAAAA8FcmpzvWk8LtDh48qMDAQGVkZKh169ZGe3h4uF599dUKX2NSVFSk2NhYderUSSEhIQoMDFTLli3VtGlTl9e2PPnkk1q/fr2++uqrGtWSm5t7fKOgSR/JbPWt0/dJjR9Qp+sAAAAAnDnKs0FOTo78/PyqPJewWQ9sNluF7Z07d9bGjRslSQ6HQxkZGQoMDJSHh4db719UVCSLxVLjcQmbAAAAACTC5hkvNTW1wnYvLy+1adPm7y2mBmrzHxQAAACAc1dtskGD3I22voWGhtZ3CQAAAABwWjXIDYIAAAAAAKcXYRMAAAAA4HaETQAAAACA2xE2AQAAAABuR9gEAAAAALgdYRMAAAAA4HaETQAAAACA2xE2AQAAAABuR9gEAAAAALgdYRMAAAAA4HaETQAAAACA2xE2AQAAAABuR9gEAAAAALgdYRMAAAAA4HaW+i4AZ4+uM1bKbPWt1TWp8QNOUzUAAAAAzmTMbAIAAAAA3I6weQb6+uuv5eXlpRYtWrh8TCaTCgsLjfNeeukl3XbbbS7X3nfffZo+fbokqbi4WA6HQ5L06KOPatKkSZIkh8Oh4uLiv+fLAAAAAGiQCJsnyMvL08CBA+Xr66uAgABt2bLF6EtNTZXJZKry+orOqWrMyvj6+uqqq67S4cOHXT5Wq1VWq1Xr1q1TRkaGmjZtqsaNG7tc6+/vL6vVKkmKjo5W165d1bVrV82bN08LFiwwjseOHVvTXwsAAAAA1FqDfGYzMjJS0dHRio6OdmlPSEhQRkaGUlJSlJ2drWbNmhl9ISEhstvttb5XVWNWxsPDQzk5OVq/fr1Lu9PpVElJiZ555hlNmTJFZrPZJdwuXLhQxcXFys3N1axZs3TvvfcqKSlJVqtVa9euVWlpqa677joVFRVpxIgRtf4uAAAAAFBTDTJsViYrK0vdunVTYGCgAgMDXfrMZrNsNptbx6zKH3/8oRdffFGS9Nlnn2nQoEHq37+/ysrKZDab5eHh4XJ+aWmpxo8fr4kTJ8rb21txcXH66quvdM0116hx48Y6cOCAiouLFRUVpYKCAjVv3twYCwAAAADcrUGFzZiYGM2ZM0eStG7dOo0ZM0bjx49XZGSkRo4caZyXmJioDh06KDk52WhLTU1VWFiYnE6ny5hJSUmaNGmSsrOzNXHiRKN98eLF1Y5Zle7du+vTTz+VJHl7exs/V2b37t3q0qWLPD09ZbFYtGfPHkVGRsrpdLoEyrFjx8rpdKq0tFQffvihLrzwwpPGKioqUlFRkXGcm5tbo5oBAAAAoFyDCpuzZs1SfHy8Bg4cqFGjRmnUqFGyWq2yWCyy2+2Kj49XWlqa3njjjZNmDiuSmZmpESNG6JVXXlHfvn01atQoo2/YsGF1GlM6/pzntm3bFBUVJUkqKSlRVFSUSktLdffdd1d4zbZt29S7d2/juGXLllq/fr1eeumlCs9/4okn5OXlVWHfzJkzFRcXV6NaAQAAAKAiDSps+vj4yMfHRxaLRb6+vi7LYm02m7y9veXl5VXj5bIrVqxQWFiYxo0bJ0mKjY3VgAHH3yvp6elZpzEl6c8//1TPnj0VGxsrSfrmm2/09NNPq6ysTG3atNG777570jWjR4/W6NGjjWsk6ejRo5ozZ46WLFnicm6/fv30xBNPVHr/adOmafLkycZxbm6ugoODa1w/AAAAADSosOluGRkZCgkJMY7Dw8PdMu6ePXvUpUsX+fr6Kj8/32g3m81q06aNJJ20nLci3t7eys7O1n333efSXlpaWumspiRj11sAAAAAqKsGGTbNZnONwlp1AgIClJ6ebhynpaWd8piStGHDBt1+++2666675HQ61bdvX02fPl1ff/218vPzVVhY6PJMZWVMJpNatWqlnTt3urR7e3u7pU4AAAAAqEyD3Io0PDxca9asUUZGhlatWiWHw1Gncfr166fk5GQlJiYqJSXFZQlrXR08eFDr16/XlVdeKavVqhdffFErVqzQihUr5OnpabzGZODAgTUaLzMz03i3ZvmnuLj4lOsEAAAAgKo0yJnN6dOna+TIkWrXrp1CQkK0e/fuGm/ec6KgoCAtWLBADz30kAoKCjR69Ght3LjxlGpbuXKlIiIidN5550mS7rjjDvn6+kqSiouL5XQ6ZTKZtHv3biUnJ7u8Z1OSCgoKjPPLyspOmtl0Op1q0qTJKdUIAAAAANVpkGGzXbt2FYbCqmYmQ0NDK1x6O2zYMA0bNsw4fv7552s8ZkXuuOMOI2jm5+fr/fffV58+fSRJ1157rYqKiuTt7a0JEyZo7dq1evPNN12udzgcRnAuKCg4afw777xT1113Xa1qAgAAAIDaMjnd8fAiaqWynWk7d+5c45nRrKws+fj4GLOYp1Nubq78/f0VPOkjma21u19q/IDTVBUAAACAv1t5NsjJyZGfn1+V5zbImc36tm3btgrbq9oh9q+aN2/upmpqbmfcDdX+BwUAAAAAEmGzXoSGhtZ3CQAAAABwWjXI3WgBAAAAAKcXYRMAAAAA4HaETQAAAACA2xE2AQAAAABuR9gEAAAAALgdYRMAAAAA4HaETQAAAACA2xE2AQAAAABuR9gEAAAAALgdYRMAAAAA4HaETQAAAACA2xE2AQAAAABuR9gEAAAAALgdYRMAAAAA4HaW+i7gbOdwOPT000/rnnvuUcuWLV36ioqKZDabZbFYZDKZKrze6XSqpKREJpNJnp6ekqQXXnhBjRs31r/+9S/jnIKCAnl7e8ts/r+/D5SUlMjpdMrLy+s0fTtXXWeslNnqW+PzU+MHnMZqAAAAAJzJmNmsgfJQV66srExlZWWSJA8PDz311FMqLCw86bohQ4YoKChI7dq1U2hoaIWfdu3aKTg4WC+88IJx3WeffaaioiLj+NChQwoLC1O3bt104YUXGp8LLrhAb731lss9ExISNH36dJe2jIwMmUwmZWRkuOX3AQAAAADVOaNnNvPy8jRy5EitWbNGjRs31ueff67LLrtMkpSamqqwsDCXEPhXFZ1T1ZiVGT9+vBYtWiSr1aqysjIVFhbqzTff1F133SVJslgsaty48UnXffHFF7X+zmVlZdq6dauuvvpqzZs3Tw6HQxdeeKEyMzNrdH16err27Nnj0ma1Wl3+FwAAAABOtzMibEZGRio6OlrR0dEu7QkJCcrIyFBKSoqys7PVrFkzoy8kJER2u73W96pqzMq8++67evfdd13atm/froceekhWq1WlpaV69tlnjTD32GOPycfHp9a1SdJ///tfFRQU6I033tCRI0dks9n08MMP6/LLL6/R9RaLxViOW658Ce+JS3ABAAAA4HQ6o9NHVlaWunXrpsDAQHXq1EmtWrUy+sxms2w2m1vHrA1fX19jKazT6VRYWJhCQ0P1zDPPyGI5nuGfeuopHTp0SAsXLpTNZlPXrl3VtGlTBQcHq2vXrjKZTCorK9P8+fO1dOlSSdKCBQs0fvx47dq1S02aNJHdbte0adP09NNPy9/f32UJroeHhw4cOOBSl8lk0qeffupy3oUXXqhGjRqpe/fuCg4OVvPmzfWf//ynTt8bAAAAAGrC5KxqHeppFhMTozlz5ri0jR8/XpGRkRo5cqRLe4cOHZScnGwcV7aMNikpSZMmTVJ2drYmTpyoGTNmyOl0avHixdWOWZH58+drypQp8vb21rFjx9SoUSOVlJSoRYsW2rFjhwoLC9WoUSOVlpaqoKBALVq0UH5+viQpKChIq1at0s8//6ylS5dq8eLFio6O1nXXXafbb79dFotFpaWluv/++9WoUSM9++yzysnJUVlZmY4dO6bu3bvryJEjko5vGpSVlaX4+HijttatW2vnzp1q0aKF0RYbG6s//vhD7733XnW//hrLzc2Vv7+/gid9xAZBAAAAQANWng1ycnLk5+dX5bn1uox21qxZio+P18CBAzVq1CiNGjVKVqtVFotFdrtd8fHxSktL0xtvvCEPD49qx8vMzNSIESP0yiuvqG/fvho1apTRN2zYsDqNefvtt+v222/X999/rzvuuEO//faby86yhw4dUosWLWQymZSXl6dGjRoZfeUznCaTSZ999plCQ0N1+PBhff755y6b+JhMJmOJ63fffaf169erqKhIxcXFmjFjhjp37lzpEti/fofc3NxTfjazqKjIZYOi3NzcUxoPAAAAQMNTr8tofXx8ZLPZZLFY5OvrK5vNJh8fH3l6espms8nb21teXl6y2Wxq0qRJteOtWLFCYWFhGjdunCIiIhQbG2v01XXMcosWLdLYsWOVlZWliRMnGu3JyckKDQ2VpJPC5okGDRqk1NRUDR8+XLNmzVJqamqF55133nnq3bu3/P391aZNG11++eUKDQ1VQUGB3nzzTZflsYcOHTppF9zs7GwlJiaqRYsWFX527txZ7XedOXOm/P39jU9wcHDNfkkAAAAA8P+dERsEuUtGRoZCQkKM4/DwcLeMm52drU8//VTbt2+Xv7+/1q1bpyVLlujmm2/WTz/9pEsuuURS5WGz/DUpNWnv3LmzOnfurJ9//lmtW7dWVFSUzGaz2rdvr0svvVRRUVGSpJUrV+ro0aMKDAx0uT45OVlz5szRHXfccdLYNputRpsETZs2TZMnTzaOc3NzCZwAAAAAauWM2CDIbDZX+QqTmgoICFB6erpxnJaWdspjOp1OTZ48WRdccIG++uorPffcc7JarXrsscfkcDi0dOlSDRw4UFLlYdPT01ObNm1SaGio1q5dq+nTpys0NFQhISFyOBwV3vfDDz9UVlaWoqKidOTIEe3evVt33HGHSkpKJEmJiYn68ssvXa7JycnRjz/+qD59+lT6XWoSNq1Wq/z8/Fw+AAAAAFAbZ0TYDA8P15o1a5SRkaFVq1ZVGsCq069fPyUnJysxMVEpKSkuy2jrqqioSKtWrVJmZqZWrVolq9WqGTNmyN/fX88884xycnKM2cbKwuaQIUOUmppa4aei50a/+OILHT58WJs3b5bT6dSAAQPUq1cvNW3aVMuXL1dubq6++OILTZs2zeW6Dz74QF26dNF5551X4XdxOp2VzrICAAAAgDudEctop0+frpEjR6pdu3YKCQnR7t27a7R5z18FBQVpwYIFeuihh1RQUKDRo0dr48aNp1Sbt7e3fv/9d2Ozn3LNmzdXVFSUkpKSdOTIEW3fvl2JiYnG85vS8aA6ePBgeXl5VXmPgwcPKiYmRtLxDYfuuecePfnkk2rUqJGWLl2qgwcPymQy6Z133lF4eLjmzZun/v37uywT/vPPP/X000/r6aefrvQ+ZWVlKi0trcNvAQAAAABqp15ffXK2cjgcuuaaazRixAjdc889ysrKUq9evXTBBRfo+eefdwmcNTFp0iR5enrqhRde0OzZs7Vy5UotX77c6H/66af16quvGrOm+fn58vDwkIeHh/Ly8vTnn3/qhx9+0HPPPaelS5fK09OzwvtYrVZ9//33uvjii2tVH68+AQAAACDV7tUnhE0d3zinIp07d650ZrS0tPSk2U53KSkpqTQw1gfCJgAAAADpLHrP5pli27ZtFbZXtfz1dAVNSWdU0AQAAACAumBmE9WqzV8vAAAAAJy7apMNzojdaAEAAAAA5xbCJgAAAADA7QibAAAAAAC3I2wCAAAAANyOsAkAAAAAcDvCJgAAAADA7QibAAAAAAC3I2wCAAAAANyOsAkAAAAAcDvCJgAAAADA7QibAAAAAAC3I2wCAAAAANyOsAkAAAAAcDvCJgAAAADA7Sz1XQDOHl1nrJTZ6lvj81PjB5zGagAAAACcyZjZBAAAAAC4HWETAAAAAOB2hE03yMvL08CBA+Xr66uAgABt2bLF6EtNTZXJZKry+orOqWpMAAAAADjT8cxmLURGRio6OlrR0dEu7QkJCcrIyFBKSoqys7PVrFkzoy8kJER2u73W96pqTAAAAAA40xE23SArK0vdunVTYGCgAgMDXfrMZrNsNptbxwQAAACAMx3LaGsgJiZGJpNJ69at05gxY2QymRQTE6PFixfLZDIpLi5OiYmJMplM6tixo8u1lS2jTUpKUkREhFq0aKH333/faK/JmBVJSEhQjx49dOONN8rf319RUVHKyMiQJC1cuFB9+vQxzs3Ozpa3t7cOHTpU118JAAAAAFSJsFkDs2bNkt1uV+/evTV79mzZ7XbNmjVLw4YNk91u19SpUzVy5EjZ7fYaPVuZmZmpESNGaOrUqdq0aZOSkpKMvrqOKUlbtmzRFVdcoW3btslqtSomJkaSNHDgQG3dulXZ2dmSpK+//lq9evVSy5YtKxynqKhIubm5Lh8AAAAAqA3CZg34+PjIZrPJYrHI19dXNptNPj4+8vT0lM1mk7e3t7y8vGSz2dSkSZNqx1uxYoXCwsI0btw4RUREKDY21uir65iSFBQUpKlTpyosLEyxsbH6/PPPVVpaKj8/P/Xt21dff/21cf9hw4ZVOs7MmTPl7+9vfIKDg2t0fwAAAAAoR9isBxkZGQoJCTGOw8PD3TJuUFCQsWS3bdu2cjgcysrKkiQNHz5cX375paTjM5tDhw6tdJxp06YpJyfH+Ozfv98t9QEAAABoOAibtWA2m+V0Ok95nICAAKWnpxvHaWlppzxm+Tjl9e3fv18Wi0UtWrSQJA0ePFirV6/Wzz//rJCQkCo3HbJarfLz83P5AAAAAEBtEDZrITw8XGvWrFFGRoZWrVolh8NRp3H69eun5ORkJSYmKiUlxWUZ7alIT0/XzJkztW/fPsXFxenGG2+Uh4eHJKlZs2bq2LGjZs6cqeHDh7vlfgAAAABQGcJmLUyfPl0pKSlq166dYmJiVFZWVqdxgoKCtGDBAsXFxalPnz7q3bu3W+rr2bOnNm/erK5du6q4uFivv/66S/+wYcO0aNGiKpfQAgAAAIA7mJzuWBeKepeQkKCEhAStXbvW7WPn5uYe3yho0kcyW31rfF1q/AC31wIAAACg/pRng5ycnGoft2Nm8yxis9kq/PTq1au+SwMAAAAAF5b6LgA1t23btgrbvby81KZNG0VHR/+t9QAAAABAZVhGi2rVZqocAAAAwLmLZbQAAAAAgHpF2AQAAAAAuB1hEwAAAADgdoRNAAAAAIDbETYBAAAAAG5H2AQAAAAAuB1hEwAAAADgdoRNAAAAAIDbETYBAAAAAG5H2AQAAAAAuB1hEwAAAADgdoRNAAAAAIDbETYBAAAAAG5H2AQAAAAAuJ2lvgvA2aPrjJUyW31rdG5q/IDTXA0AAACAMxkzmwAAAAAAtyNsnmWOHTum/fv31/j8kpIS4+fS0lI5HI7TURYAAAAAuCBsnqGeeOIJvfTSS8ZxUVGRysrK9NNPP+mqq66q8Jr//e9/2rJli3G8a9cuXXjhhcrNzZUkLVy4UFdfffXpLRwAAAAARNh0kZeXp4EDB8rX11cBAQEuwS01NVUmk6nK6ys6p6oxK5Odna233npL119/vcrKylRUVKTPPvtM/fr1k8ViUZs2bSq87tNPP1VMTIwkqaCgQO3bt9e1116rrVu3SpLee+89TZgwQWVlZSosLJTT6ay2FgAAAACoiwa5QVBkZKSio6MVHR3t0p6QkKCMjAylpKQoOztbzZo1M/pCQkJkt9trfa+qxqxMbGysnE6nBg8erLKyMg0ZMsRYDrto0SIdPHhQL774okpKSnT99dfr0ksvlSTdeOONmjBhgjIyMjR48GAdPHhQZrNZS5cuVXp6utq1a6eHH35YDz74oEpLS7V582YFBwfX+jsBAAAAQHUaZNisTFZWlrp166bAwEAFBga69JnNZtlsNreOWZGVK1dq+fLl+u2339S0aVNJ0tGjRxUcHKznn39e6enp8vb2Vtu2beVwONSkSRPj2qCgIO3du1eBgYHasmWL1q9fr6NHj+qHH37QnDlz9NZbb0mSfH19K12KCwAAAADuYHI2oLWUMTExmjNnjkvb+PHjFRkZqZEjR7q0d+jQQcnJycZxamqqwsLCTlp6mpSUpEmTJik7O1sTJ07UjBkz5HQ6tXjx4mrHrMju3bt1xx136NChQ/L09FRBQYFeeuklzZs3T19//bVWrVql559/Xl999ZXLdcnJydqzZ488PT3Vu3dvNWnSRF27dtX111+vCy64wOV7LFiwQHv27Km0hqKiIhUVFRnHubm5Cg4OVvCkj3j1CQAAANCA5ebmyt/fXzk5OfLz86vy3AY1szlr1izFx8dr4MCBGjVqlEaNGiWr1SqLxSK73a74+HilpaXpjTfekIeHR7XjZWZmasSIEXrllVfUt29fjRo1yugbNmxYncbs1KmTtmzZopiYGPXs2dNY6nvLLbdIkvLz82WxnPzPlpWVpZ07d2rmzJn673//q06dOsnLy0uffPKJvv76a+O8wsJCeXl5VVnDzJkzFRcXV22tAAAAAFCZBrVBkI+Pj2w2mywWi3x9fWWz2eTj4yNPT0/ZbDZ5e3vLy8tLNpvNZXlqZVasWKGwsDCNGzdOERERio2NNfrqOqZ0fHMfSXI6nSooKNALL7yg4OBgBQUFacyYMfrmm28UFBSkNm3aGLOWvXv31rRp0+Tr6ytvb29Jkslk0uzZs7Vz507js3jxYpnNVf+zT5s2TTk5OcanNq9aAQAAAACpgc1sultGRoZCQkKM4/Dw8FMeMzc3V+eff76OHTumJUuWaNq0aXr99de1ePFieXh4aObMmfrss880Z84chYWFVTjGiTvi3nXXXfLx8TGOi4uLq92kyGq1ymq1nvJ3AQAAANBwNciwaTab3fLaj4CAAKWnpxvHaWlppzymn5+fDh48eNIyWul4UPzxxx91/fXX69NPP9Xbb79d5VglJSV65513NHDgQKPthx9+0B133HHKdQIAAABAVRrUMtpy4eHhWrNmjTIyMrRq1So5HI46jdOvXz8lJycrMTFRKSkpLsto3eX555/Xhx9+KEl68cUX1a5dO33wwQdasmSJvv32W5dzS0pKVFJSosOHD0uSjh07prvuukuhoaHGZ/DgwSouLnZ7nQAAAABwogY5szl9+nSNHDlS7dq1U0hIiHbv3l2jzXv+KigoSAsWLNBDDz2kgoICjR49Whs3bnRLjUVFRXr22Wfl5+enDz74QB9++KFeeOEFff/992rVqpWeeeYZ3Xzzzfrmm2/UuXNnZWVlacSIEerZs6fuv/9+XXDBBXrppZd0/vnny8/PTx4eHnI4HCosLFReXp6++uorXXfdddU+vwkAAAAAddGgXn1yNunVq5dat26td999Vw8++KA+/fRTLV++XL169TLOGTdunJYsWaJffvlFP/30k5YsWaLExERJ0uLFi/XRRx9p9+7dOnz4sI4dO6aSkhKZTCaZzWZddtllWr9+fY1qKd/emFefAAAAAA1bbV59QtisBzabrcL2zp07GzOj6enpatWqlTw8PPTuu+/q+uuvV3BwsMv5TqdTq1ev1nXXXXda6yVsAgAAAJAIm2e81NTUCtu9vLzUpk2bv7eYGqjNf1AAAAAAzl21yQYN8pnN+hYaGlrfJQAAAADAacXuMAAAAAAAtyNsAgAAAADcjrAJAAAAAHA7wiYAAAAAwO0ImwAAAAAAtyNsAgAAAADcjrAJAAAAAHA7wiYAAAAAwO0ImwAAAAAAtyNsAgAAAADcjrAJAAAAAHA7wiYAAAAAwO0ImwAAAAAAt7PUdwE4e3SdsVJmq2+Nzk2NH3CaqwEAAABwJmNmEwAAAADgdoTNc9zHH3+sH374ob7LAAAAANDAsIz2DHXppZcqNTVVjRs3rrA/OztbUVFRWrx4cZXjvPzyy+rUqZPeeeed01EmAAAAAFSImc0T5OXlaeDAgfL19VVAQIC2bNli9KWmpspkMlV5fUXnVDVmVby8vPTiiy8qNTW1ws99990nLy8v4/xHH31UNptNXbt2dfnk5ubqv//9r0tbhw4dZDKZlJ+fX4vfDgAAAADUXIOc2YyMjFR0dLSio6Nd2hMSEpSRkaGUlBRlZ2erWbNmRl9ISIjsdnut71XVmFUxmUx68MEHFRsbW2F/dna2brrpJuPYbDZr4MCBmj9/vsrKyvTEE0/I19dXjz76qDIzM3XTTTfprrvu0ujRo5WRkaGwsDB5eHjU+vsAAAAAQE00yLBZmaysLHXr1k2BgYEKDAx06TObzbLZbG4dsypOp1MvvvjiSYG43PTp05WWlmYcDxs2TAUFBVq3bp2mTJmiJk2aaPbs2ZKkVq1aKTY2VlOmTNHjjz+uTz75RP/5z38ImwAAAABOG5PT6XTWdxF/l5iYGM2ZM8elbfz48YqMjNTIkSNd2jt06KDk5GTjODU1VWFhYfrrryspKUmTJk1Sdna2Jk6cqBkzZsjpdGrx4sXVjlmVwYMHa8eOHVWeM2jQIL322mvGcVlZmb7++mvt379fY8eOPen84uJiLVq0SHfccUeVS4KLiopUVFRkHOfm5io4OFjBkz7i1ScAAABAA5abmyt/f3/l5OTIz8+vynMbVNgsKChQUVGRBg4cqFGjRmnUqFGyWq2yWCw6duyY4uPjlZaWpjfeeEMeHh5q0qSJcW1FYTMzM1PnnXeeXnnlFfXt21ejRo3Sli1b5HQ6VVJSUu2YVTl69Kjy8/MVEBAgSdq5c6fy8/PVo0ePSq/5+eefNWzYMFksFpnNFT+Oe+DAAT311FOaMGFCpePExsYqLi7upHbCJgAAANCw1SZsNqhltD4+PvLx8ZHFYpGvr6/LslibzSZvb295eXnVeLnsihUrFBYWpnHjxkk6HtIGDDgesjw9Pes0Zrlp06bp66+/1o8//qhGjRrpgw8+0P79+7Vw4UJJksPhUGlpqaxWq3FNt27d9Mknn+jAgQOVjhsfH++ysVBl9548ebJxXD6zCQAAAAA11aDCprtlZGQoJCTEOA4PD3fLuKtWrdJbb72lRo0aqW3btpKkwsJClZWV6fPPP5d0fMlsSUmJMjMz5e/vb1w7adIkdevWTb17965w7Pvuu0/du3ev8v5Wq9UlxAIAAABAbTXIsGk2m0969rIuAgIClJ6ebhyfuGFPXW3dulVDhgzRSy+9pAkTJhjPVk6fPl0HDhxQQkKCcW5ZWZnLctnc3Fxt2LBBv/zyi/7zn/9UeZ/Vq1e7LRwDAAAAwF81yLAZHh6uNWvWKCoqSr/88ov69u1bp51Z+/Xrp3vuuUeJiYnq06dPpa8pqY2OHTvqnXfeUZ8+fdS8eXNj2W9OTo5KS0v1zTffqKysTEVFRRo+fLjeeOMN41o/Pz8VFBRUOf7//vc/BQUFqVWrVqdcKwAAAABUpkGGzenTp2vkyJFq166dQkJCtHv37jqFzaCgIC1YsEAPPfSQCgoKNHr0aG3cuPGUavPy8lJUVJQaN26sI0eOuNT815lNp9Op/Px8+fj4VLm7rCR99913RlgNDw9X48aNT6lOAAAAAKhKg9qN9mywc+dOdevWTb6+vvLx8THay8rKJMll2WxxcbHy8/N14MABtW7duspx7777bn366afq2LGjHnvsMd1www01rql8xyl2owUAAAAaNl59coarbGfazp07a8OGDSorK6vTTOvpUpv/oAAAAACcu3j1yRlu27ZtFbZ7eXnJZDKdUUETAAAAAOqCsFkPQkND67sEAAAAADitzNWfAgAAAABA7RA2AQAAAABuR9gEAAAAALgdYRMAAAAA4HaETQAAAACA2xE2AQAAAABuR9gEAAAAALgdYRMAAAAA4HaETQAAAACA2xE2AQAAAABuR9gEAAAAALgdYRMAAAAA4HaETQAAAACA21nquwCcPbrOWCmz1bfKc1LjB/xN1QAAAAA4kzGzCQAAAABwO8LmOSY7O1v//e9/Zbfb67sUAAAAAA0YYdMN8vLyNHDgQPn6+iogIEBbtmwx+lJTU2Uymaq8vqJzqhqzMkuWLFFoaKjGjh2roKAgLVmypMLzoqKilJCQUP0XAwAAAIA6ImzWQmRkZIUhLSEhQRkZGUpJSdG6desUEhJi9IWEhNRplrGqMSuSk5Oje+65R99++61+/vlnzZ49Ww899NBJ5y1YsEArV66sdT0AAAAAUBtsEOQGWVlZ6tatmwIDAxUYGOjSZzabZbPZ3DpmRXJzc/XKK6+oe/fukqSLL75YWVlZLuccOXJEU6ZMUYcOHWpdDwAAAADUBjObNRATEyOTyaR169ZpzJgxMplMiomJ0eLFi2UymRQXF6fExESZTCZ17NjR5drKltEmJSUpIiJCLVq00Pvvv2+012TMigQHB+u2226TJJWUlGjWrFkaMmSIyzlTpkzRkCFD1LNnzyrHKioqUm5urssHAAAAAGqDmc0amDVrluLj4zVw4ECNGjVKo0aNktVqlcVikd1uV3x8vNLS0vTGG2/Iw8Oj2vEyMzM1YsQIvfLKK+rbt69GjRpl9A0bNqxOY5bbvn27rrnmGnl5eWn37t1G+zfffKPVq1frl19+0YQJE6ocY+bMmYqLi6vxPQEAAADgr5jZrAEfHx/ZbDZZLBb5+vrKZrPJx8dHnp6estls8vb2lpeXl2w2m5o0aVLteCtWrFBYWJjGjRuniIgIxcbGGn11HbNc9+7d9dVXX6l9+/YaO3asJKmwsFDjx4/Xm2++WaOxpk2bppycHOOzf//+Gt8fAAAAACRmNutFRkaGy4Y/4eHhbhvbZDLpkksuUWJiosLDw5Wdna0XXnhBl112mQYMGFCjMaxWq6xWq9tqAgAAANDwEDZrwWw2y+l0nvI4AQEBSk9PN47T0tJOecx169YpKSlJL7zwgiTJy8tLJpNJZrNZCxcu1KFDh4yNivLz8/XRRx9p8+bNeuONN0753gAAAADwV4TNWggPD9eaNWsUFRWlX375RX379q3V85Tl+vXrp3vuuUeJiYnq06ePyzLaujr//PM1d+5ctW/fXv3799f06dPVr18/+fn56bvvvlNpaalx7oMPPqiePXsqOjr6lO8LAAAAABXhmc1amD59ulJSUtSuXTvFxMSorKysTuMEBQVpwYIFiouLU58+fdS7d+9Tri0wMFAff/yxXn31VXXp0kX5+fnGLrdBQUEKDQ01Po0bN1aLFi3UokWLU74vAAAAAFTE5HTHulCc03Jzc+Xv76/gSR/JbPWt8tzU+Jo9FwoAAADg7FOeDXJycuTn51fluSyjPYuUP3P5V507d9bGjRv/3mIAAAAAoAqEzbPItm3bKmz38vL6W+6/M+6Gav96AQAAAAASYfOsEhoaWt8lAAAAAECNsEEQAAAAAMDtCJsAAAAAALcjbAIAAAAA3I6wCQAAAABwO8ImAAAAAMDtCJsAAAAAALcjbAIAAAAA3I6wCQAAAABwO8ImAAAAAMDtCJsAAAAAALcjbAIAAAAA3I6wCQAAAABwO8ImAAAAAMDtCJsAAAAAALez1HcBOH0cDocGDBigBx54QDfccMMpj9d1xkqZrb6V9qfGDzjlewAAAAA4NzCzeQ5LSEjQypUrtWTJkvouBQAAAEADQ9g8QV5engYOHChfX18FBARoy5YtRl9qaqpMJlOV11d0TlVjnk579uzR5MmT9fHHH2vdunWaPXv233JfAAAAAJAa6DLayMhIRUdHKzo62qU9ISFBGRkZSklJUXZ2tpo1a2b0hYSEyG631/peVY15uhw6dEg33XST7rvvPg0bNkwRERGKjIzU0aNHNXXq1NN+fwAAAABgZvMEWVlZ6tatmwIDA9WpUye1atXK6DObzbLZbG4d83TYsmWLevbsqd69e+uZZ57RTTfdpGPHjmnlypV67rnndP3112vPnj2ntQYAAAAAaFBhMyYmRiaTSevWrdOYMWNkMpkUExOjxYsXy2QyKS4uTomJiTKZTOrYsaPLtZUto01KSlJERIRatGih999/32ivyZgVKSsrU2FhoUpLS6s91+l0qqioSE6nU6mpqbr77rvVq1cvjRkzRnPnzpUkJScn6+jRo+rRo4d++uknHT16VB07dtTgwYNVXFxc7T0AAAAAoC4a1DLaWbNmKT4+XgMHDtSoUaM0atQoWa1WWSwW2e12xcfHKy0tTW+88YY8PDyqHS8zM1MjRozQK6+8or59+2rUqFFG37Bhw+o05saNG3XllVfW6nvt27dPxcXF+vXXX7Vu3Tr16tXL6PP29pbZfPxvCqGhodqwYYMWLFigrKwseXl5VTheUVGRioqKjOPc3Nxa1QMAAAAADSps+vj4yMfHRxaLRb6+vi7LYm02m7y9veXl5VXj5bIrVqxQWFiYxo0bJ0mKjY3VgAHHX//h6elZpzHPP/98ffDBB/Ly8qo0DJYrLi5WcXGxWrRoocaNG2vdunXVjm82mzV69Ogqz5k5c6bi4uJqVC8AAAAAVKRBhU13y8jIUEhIiHEcHh5+ymMGBATo9ttvP+VxTsW0adM0efJk4zg3N1fBwcH1WBEAAACAs02DDJtms1lOp/OUxwkICFB6erpxnJaWdspjngmsVqusVmt9lwEAAADgLNagNggqFx4erjVr1igjI0OrVq2Sw+Go0zj9+vVTcnKyEhMTlZKSotjYWPcW6gbuCNUAAAAAUFsNMmxOnz5dKSkpateunWJiYlRWVlancYKCgrRgwQLFxcWpT58+6t27t5srPXXFxcU12tkWAAAAANzJ5GTq65wWHh6uV155RYMGDarzGLm5ufL391fwpI9ktvpWel5q/IA63wMAAADAma88G+Tk5MjPz6/KcxvkM5v1rbKdaTt37qyNGze69V4pKSluHQ8AAAAAaoKwWQ+2bdtWYXt1rzoBAAAAgLMFy2hRrdpMlQMAAAA4d9UmGzTIDYIAAAAAAKcXYRMAAAAA4HaETQAAAACA2xE2AQAAAABuR9gEAAAAALgdYRMAAAAA4HaETQAAAACA2xE2AQAAAABuR9gEAAAAALgdYRMAAAAA4HaETQAAAACA2xE2AQAAAABuR9gEAAAAALgdYRMAAAAA4HaW+i4AZ4+uM1bKbPU9qT01fkA9VAMAAADgTMbMJgAAAADA7QibZ7jCwkJ9+umntb7ut99+08qVK1VaWur+ogAAAACgGiyjPcM9/PDD+vHHH9W/f39ZrdYaX/fEE0+otLRU11577WmsDgAAAAAqxszmCfLy8jRw4ED5+voqICBAW7ZsMfpSU1NlMpmqvL6ic6oaszqzZ8/W7NmzlZKSog4dOig0NFQhISGKiIjQ3r17K70uKSlJH374oTZs2KCIiAiFhoYqNDRU1113nYqLi2t8fwAAAACoqwY5sxkZGano6GhFR0e7tCckJCgjI0MpKSnKzs5Ws2bNjL6QkBDZ7fZa36uqMStTWFioRx99VKtXr9bOnTvVqVMnSVJRUZGioqI0ceJERUREVHjt1q1bdffdd2vLli269NJLJR0PvO3atdNjjz0mLy+vWn8HAAAAAKitBhk2K5OVlaVu3bopMDBQgYGBLn1ms1k2m82tY1Zm6NChOnjwoFJSUnTFFVcY7aWlpSooKNDWrVs1ZswYSdKmTZvUsWNHSdL8+fN1zz336I033jCCpiQ9/vjj6tevn/r27Vvr+gEAAACgLhrUMtqYmBiZTCatW7dOY8aMkclkUkxMjBYvXiyTyaS4uDglJibKZDIZAa5cZctok5KSFBERoRYtWuj999832msyZmXmzp2rxMREtWjRQtnZ2crOztamTZvUokULORwOo83b21uenp6SpAMHDmjGjBmKjIzU3XffbSyd9ff3V0JCgjZt2qTQ0FB5e3tr8eLFVd6/qKhIubm5Lh8AAAAAqI0GNbM5a9YsxcfHa+DAgRo1apRGjRolq9Uqi8Uiu92u+Ph4paWl6Y033pCHh0e142VmZmrEiBF65ZVX1LdvX40aNcroGzZsWJ3GlKSgoCAdPXq0RueWjxkUFKQ9e/bo/fffV1lZmZKSkiRJjzzyiLy9vRUbGyvp+BLiJk2aVDnmzJkzFRcXV6P7AwAAAEBFGlTY9PHxkY+PjywWi3x9fV2WxdpsNnl7e8vLy6vGy2VXrFihsLAwjRs3TpIUGxurAQMGSJI8PT3rNGa53NxcpaenKzQ0VJJUUlKizMxM41iSDh065HKN2Vyzierqzps2bZomT57sUktwcHDNCgcAAAAANbCw6W4ZGRkKCQkxjsPDw9029p9//qnLLrtMGzZskCQlJycrKipKqampxjmtW7eu8Npvv/1WXbt2dWn7+OOPJUn79u1TUVFRlfe2Wq21es0KAAAAAPxVgwybZrNZTqfzlMcJCAhQenq6cZyWlnbKY5bbtWuXfvrpp1rNbJa76qqrjGW0fzV37lyXgAwAAAAAp0OD2iCoXHh4uNasWaOMjAytWrVKDoejTuP069dPycnJSkxMVEpKivFcpDt8/vnneuutt5SamqrU1FStXr1aQUFBxnFqaqpatmxZ63Hvvvvuk2Y9AQAAAMDdGmTYnD59ulJSUtSuXTvFxMSorKysTuMEBQVpwYIFiouLU58+fdS7d2+31Ld69Wpt3bpVQ4YMMdoKCwtdZmPz8/NVWFh40g65Xl5e2rNnj3Jycioc2+l0atKkSXrkkUfcUisAAAAAVMTkdMd6UrhNWVmZLr/8cv3zn//UfffdZ7R/9913GjZsmP788099+OGHGjlypNq3b69ffvlFFsv/rYbOzMzUDTfcoH379lX4qhaz2awLLrhA8+fPV9u2bWtUU25urvz9/RU86SOZrb4n9afGD6jDNwUAAABwtinPBjk5OfLz86vyXMJmPahsZ9rOnTtr48aNys7Olp+fX6W7xpaWlio1NVXh4eEVBkp3I2wCAAAAkAibZ7wTd5Q9kZeXl9q0afP3FlMDtfkPCgAAAMC5qzbZoEHuRlvfTtxRFgAAAADORQ1ygyAAAAAAwOlF2AQAAAAAuB1hEwAAAADgdoRNAAAAAIDbETYBAAAAAG5H2AQAAAAAuB1hEwAAAADgdoRNAAAAAIDbETYBAAAAAG5H2AQAAAAAuB1hEwAAAADgdoRNAAAAAIDbETYBAAAAAG5nqe8CcPboOmOlzFbfk9pT4wfUQzUAAAAAzmTMbAIAAAAA3I6wCQAAAABwO8LmGWjt2rV6/vnnlZubq6ZNm0qSSktLlZWVpbS0NK1bt04vvfSS+vXrp9dee63Ksa699lrNnTv37ygbAAAAAAyEzRPk5eVp4MCB8vX1VUBAgLZs2WL0paamymQyVXl9RedUNWZljhw5oh9//FG+vr6yWq2SpI0bNyokJETDhw/XCy+8oF9//VV9+vRRWFiYcV1paelJY/n4+MjLy+ukdofDUW0dAAAAAFBXDXKDoMjISEVHRys6OtqlPSEhQRkZGUpJSVF2draaNWtm9IWEhMhut9f6XlWNWRkPDw/5+Pi4tDVu3FiXXXaZ1q5dW+l1HTp00MGDB+Xp6SlJKioqUlFRkb788ktNmDBBHh4eRvu4ceP073//u9bfBwAAAABqokGGzcpkZWWpW7duCgwMVGBgoEuf2WyWzWZz65iV+evsaElJiSwWi7Kzs08Km126dFHLli0lSSkpKS59559/vrKysuTh4aEnnnhC9913X63rBwAAAIC6aFDLaGNiYmQymbRu3TqNGTNGJpNJMTExWrx4sUwmk+Li4pSYmCiTyaSOHTu6XFvZMtqkpCRFRESoRYsWev/99432moxZGZPJpGXLlunCCy9UixYt1LlzZx09elRHjhzRoEGDtGzZMiUlJemWW27R3r17Kxxj7dq18vT01BVXXKFhw4Zp0aJFNf49FRUVKTc31+UDAAAAALXRoMLmrFmzZLfb1bt3b82ePVt2u12zZs3SsGHDZLfbNXXqVI0cOVJ2u71Gz1ZmZmZqxIgRmjp1qjZt2qSkpCSjr65jSsfD5o033qidO3dq586d2rNnjzw9PdWlSxd17NhREyZM0Isvviin06muXbtWOEZ8fLwmTpwoSbr88stlt9u1cePGGt1/5syZ8vf3Nz7BwcE1ug4AAAAAyjWosOnj4yObzSaLxSJfX1/ZbDb5+PjI09NTNptN3t7e8vLyks1mU5MmTaodb8WKFQoLC9O4ceMUERGh2NhYo6+uY0rHZxaXLVumrl27qmvXrvr555+Vk5MjPz8/derUSdu2bVNaWpoaN25c4ZhffPGF9u3bpzvvvNNoe+aZZzRx4kQVFxdXe/9p06YpJyfH+Ozfv79GdQMAAABAuQYVNt0tIyNDISEhxnF4eLhbxs3Pz9fo0aO1c+dONW/eXE6nU/v371fr1q3Vp08frVq1SqtXr1bv3r0rrGn8+PF67bXXjI2CJGnIkCFq3bq1YmJi5HQ6q7y/1WqVn5+fywcAAAAAaqNBhk2z2Vxt4KqJgIAApaenG8dpaWmnPKYkHThwQG3atJEkOZ1Omc1mbdu2TR07dtQtt9yizz77THPnztWQIUNcrsvOztZNN92kO+64Q1deeaXLd3Q4HHr77be1adMmjR49WgUFBW6pFQAAAAAq0iDDZnh4uNasWaOMjAytWrWqzu+c7Nevn5KTk5WYmKiUlBSXZbSnYvfu3cZzkk6nU06nU59//rn69u0rm82mK664QmlpabrpppuMa3777Tf16NFDnTp10q233qrmzZurRYsW+uqrrzRhwgQ1b95ckZGR+uabb7Rnzx4NHz7cLbUCAAAAQEUaZNicPn26UlJS1K5dO8XExKisrKxO4wQFBWnBggWKi4tTnz59KlzWWltlZWVas2aNLrvsMklSaWmpPvnkE/n6+qpjx45KTEzUF198IS8vLz3wwAPGDGVQUJCmTJmid999V926dVN+fr6ysrLUt29fvfLKK8rOztavv/6qVq1aae3atXr77bdPuVYAAAAAqIzJ6Y71pHCbHTt26LbbbtPPP/8sSerRo4fuuecetWnTRosXL9by5cu1ZMkSde7cWYMHD1Zubq5++ukn+fj4VDheZGSkRowYoX/96191rik3N/f4rrSTPpLZ6ntSf2r8gDqPDQAAAODsUZ4NyjcwrQphsx7YbLYK2zt37qyNGzeqqKhIVqv1pP4dO3aoefPmatu2rSSppKREu3fvVvfu3U9nuYRNAAAAAJIIm2e81NTUCtu9vLyMjYHOJLX5DwoAAADAuas22cDyN9WEE4SGhtZ3CQAAAABwWjXIDYIAAAAAAKcXYRMAAAAA4HaETQAAAACA2xE2AQAAAABuR9gEAAAAALgdYRMAAAAA4HaETQAAAACA2xE2AQAAAABuR9gEAAAAALgdYRMAAAAA4HaETQAAAACA2xE2AQAAAABuR9gEAAAAALidpb4LwNmj64yVMlt9T2pPjR9QD9UAAAAAOJMxswkAAAAAcDvCZgNx+PBhPfPMMyoqKqrvUgAAAAA0AITNM1B2drbGjx+vzMzMk/oKCgr0008/6e2339bYsWN19OhRo6+4uNjlXIfDIafTaVwXGxsrT0/P01s8AAAAAIiw6SIvL08DBw6Ur6+vAgICtGXLFqMvNTVVJpOpyusrOqeqMSvj6ekph8Ohiy++WBs2bNC4ceN0+eWXKyQkRP7+/nrooYeUkpKiHj16yG63G9dFRUWpUaNGstlsatKkiaxWq9asWWOM6evrK7OZf3IAAAAAp1+D3CAoMjJS0dHRio6OdmlPSEhQRkaGUlJSlJ2drWbNmhl9ISEhLsGupqoaszKNGjXSvHnz9Oqrr8rf318TJ06UxWLReeedp6uvvlqPP/64IiMjT7quPFie6JtvvtHUqVNVXFysoqIiTZ8+XZJktVr1+OOP1/r7AAAAAEBNNMiwWZmsrCx169ZNgYGBCgwMdOkzm82y2WxuHbMyP/30k7p166b7779fJSUlMpvN8vDwqPDc4uJiWSyWSmcs/fz8FBoaqqNHj8rT01OhoaHKysrSv//9b8ImAAAAgNPG5Cx/qK8BiImJ0Zw5c1zaxo8fr8jISI0cOdKlvUOHDkpOTjaOU1NTFRYWpr/+upKSkjRp0iRlZ2dr4sSJmjFjhpxOpxYvXlztmBUpKytTnz59VFBQoMTERC1cuFDz58+XxXL87wIZGRlq2rSpvL29JUmlpaVatmyZVqxYoddff12enp4qKChQo0aNVFRUpEsuuURJSUlKTk7WP/7xD/3+++/atWuXhg8frl27dlVYQ1FRkctGQrm5uQoODlbwpI949QkAAADQgOXm5srf3185OTny8/Or8twGNbM5a9YsxcfHa+DAgRo1apRGjRolq9Uqi8Uiu92u+Ph4paWl6Y033qh0JvFEmZmZGjFihF555RX17dtXo0aNMvqGDRtWpzHNZrO+/fZbPfPMM7rtttu0detWxcfHG/09e/ZUfHz8SctoL7nkEj322GNatGiR3nnnHa1atcql/9ChQ2rZsqWk48+RNmrUqNIaZs6cqbi4uGprBQAAAIDKNKjdYnx8fGSz2WSxWOTr6yubzSYfHx95enrKZrPJ29tbXl5exgY71VmxYoXCwsI0btw4RUREKDY21uir65iSZLFYNGPGDC1YsKDWG/osWrRI48aN0969e12WySYnJys0NFRS9WFz2rRpysnJMT779++vVQ0AAAAA0KDCprtlZGQoJCTEOA4PD3fb2E6nU7fffruWLl2qRx99VE2bNlVoaKgOHjyo6OhohYaGymq16osvvjCu2bt3r3bv3q1hw4apdevWeuedd7R582ZJx58DveSSSyRVHzatVqv8/PxcPgAAAABQGw0ybJrN5pOevayLgIAApaenG8dpaWmnPGa55cuXq7CwUEOHDpWnp6emTp2q1NRUl89FF11kPLtZUlKie++9V1dffbU+/PBDvfzyy/Lz89O0adNUUlKi5cuXa8CA489WVhc2AQAAAOBUNciwGR4erjVr1igjI0OrVq2Sw+Go0zj9+vVTcnKyEhMTlZKS4rKM9lSUlJTo0UcfVWxsrDw8PKp8v2f5MtsjR45oy5YtSk5O1oYNG9S0aVO98MIL+vPPP/XYY4+pU6dO6tKliyTCJgAAAIDTr0FtEFRu+vTpGjlypNq1a6eQkBDt3r27Rpv3/FVQUJAWLFighx56SAUFBRo9erQ2btx4yvXFxsbKZDLp1ltvlXR8Se3MmTP1+uuvu5x36NAhY4a2VatW+vPPP41da8s5HA6NGTNGmzdv1oEDB7Rr1y59/PHHFb6nEwAAAADcpUG9+uRsUFZWpvHjx6t///4aOnSoJOnRRx+Vn5+fHnnkEZdze/bsqdjYWEVFRVU4Vl5enq644grNnDlTgwYN0q5du3TjjTeqT58+evHFF9W8efMa1VS+vTGvPgEAAAAattq8+oSwWQ9sNluF7Z07d65wZrSwsFAmk0lWq7XW9yotLT1ptrO2avMfFAAAAIBzF+/ZPMNt27atwnYvL68K28s3AaqLUw2aAAAAAFAXJJF6UP6+SwAAAAA4VzXI3WgBAAAAAKcXYRMAAAAA4HaETQAAAACA2xE2AQAAAABuR9gEAAAAALgdYRMAAAAA4HaETQAAAACA2xE2AQAAAABuR9gEAAAAALgdYRMAAAAA4HaETQAAAACA2xE2AQAAAABuR9gEAAAAALidpb4LwNmj64yVMlt9XdpS4wfUUzUAAAAAzmTMbJ6hcnJy5HA43DZedna2Dh486LbxAAAAAKAqhM0zVLt27fTrr78ax0lJSerdu7fLOcOGDdNbb73l0nb33Xdr4cKFxnFBQYEk6bPPPtPIkSNPY8UAAAAA8H9YRnuCvLw8jRw5UmvWrFHjxo31+eef67LLLpMkpaamKiwsTE6ns9LrKzqnqjGrYrFY9Mwzz6hJkyaSpP3792vfvn2KiYkxztm+fbuioqKM47179+o///mP4uLi5HA45HA4NHv2bCUnJ+vaa69VmzZtav07AQAAAIC6aJBhMzIyUtHR0YqOjnZpT0hIUEZGhlJSUpSdna1mzZoZfSEhIbLb7bW+V1VjVuWzzz6rdhnt7bffrvDwcOP4wQcflMVi0RVXXCGHw6H777/fJeT++uuveuGFF1RSUqJbbrlFERERtf4+AAAAAFATDTJsViYrK0vdunVTYGCgAgMDXfrMZrNsNptbx6zMgQMH1L9/f5e277//Xk6nU7169XJpj4mJUXx8vObNm6f9+/frjz/+kJeXl6TjM61PPvmk3nrrLW3cuFGNGzdWUFCQSktL5ePjU+vvAgAAAAA11aDCZkxMjObMmSNJWrduncaMGaPx48crMjLS5XnGxMREdejQQcnJyUZbZctok5KSNGnSJGVnZ2vixIlG++LFi6sdszImk0mlpaU6evSoJKl169by9PRUWVmZGjdurAMHDkj6v5lMSerQoYNKSkp0/vnny9PTUxaLRZMnT9awYcM0atQo5efnq7i4uEbPbRYVFamoqMg4zs3NrfYaAAAAADhRg9ogaNasWbLb7erdu7dmz54tu92uWbNmadiwYbLb7Zo6dapGjhwpu92uLVu2VDteZmamRowYoalTp2rTpk1KSkoy+uo6pnQ8bP6VxWKpsN3b21uSdOWVV2rHjh3q2LGj3n77be3evVvjxo3Tu+++K0nKz883gml1Zs6cKX9/f+MTHBxco+sAAAAAoFyDmtn08fGRj4+PLBaLfH19XZbF2mw2eXt7y8vLq8bLZVesWKGwsDCNGzdOkhQbG6sBA46/d9LT07NOY0qSw+FQfn6+QkNDJUmHDh2SJJWWlurgwYNGu91u10MPPSRJKisrU3FxsfFzfn6+HnvsMS1ZskSSdPToUZWWlmr58uVyOBy65JJLXMLxiaZNm6bJkycbx7m5uQROAAAAALXSoMKmu2VkZCgkJMQ4PnGznlNx7NgxNW3aVKmpqZKOL6Mtb+/QoYN++eUXSceX0ZbbtWuXrr/++v/X3r1H13Tn/x9/nSTOSVKSIyQtcpFqK1UspRlavuho9eLSGi3FakcpwurSjLqWkcRQadWtVCnTYiatMehl1ESbBsOK1KVR4xJGKuISlOZCJSHJ/v3h56ymIpeTfYKe52Ot/cf+7P357PfxPied9+zP/mzl5uYqLS1NFotFq1ev1nPPPScPDw+NHj1ae/fu1dq1a1WvXj3VqVPnhte32Wyy2WymfBYAAAAA7skti00PD48KX2FSVUFBQTp16pRjPysrq8ZjStLp06eVm5t73Z3NU6dO6ciRI+Xe2WzZsqWys7P15JNPauLEieratatjvPPnz+vAgQPq1KmTkpKSNHnyZFPiBAAAAIAbcatnNq9p1qyZkpOTlZ2draSkpEpfMXIj3bt3V3p6ulasWKGMjAzFxsaaEt+OHTvUo0cPZWZmKjMzU4GBgZKurkg7atQoR/u16bu/du21J6mpqZKuTot95plnNG/ePL311ls6fPiwKXECAAAAwI24ZbE5ZcoUZWRkKCwsTFFRUSotLXVqnODgYCUkJCguLk6dOnVSx44daxxbaWmpVq5cqccff1z5+flau3atcnJy5OXlpYSEBHXu3Nlx7o8//njdokFFRUUaOXKk0tPTFRwcrNmzZ+vLL7/U/Pnz1apVK40YMUK9evUqc0cWAAAAAMxmMcyYTwrTJCcna9CgQUpPT5fNZtNjjz2mXr166c4779Sf//xnZWRkyGq16sUXX9SaNWu0fv16devWTdLVO5rh4eHq3bu3YmJiNHz4cH333Xf6+uuvdd9990m6ushQ7969deDAAe3fv1933HFHpTHl5+dfXZU2erU8bL5ljmXG9zD/HwEAAADALelabZCXlyc/P78Kz6XYvAlutDJtixYtlJKSokuXLsnX1/e647m5uY6+Z8+eVd26da877/jx4woJCZFhGFq4cKEGDRqkgICAMudcvnxZ27dvV5cuXaoUL8UmAAAAAIli85Z3bZXZX7NarWrcuHHtBlMF1flCAQAAAPjtqk5t4Jar0d5s11aTBQAAAIDfKrdcIAgAAAAA4FoUmwAAAAAA01FsAgAAAABMR7EJAAAAADAdxSYAAAAAwHQUmwAAAAAA01FsAgAAAABMR7EJAAAAADAdxSYAAAAAwHQUmwAAAAAA01FsAgAAAABMR7EJAAAAADAdxSYAAAAAwHQUmwAAAAAA03nd7ABw+2gZs1EeNt8ybZnxPW5SNAAAAABuZdzZvI1s2bJFycnJ1e535MgR7dq1ywURAQAAAED5KDZvI++++662bt1a7X4fffSRJk+e7IKIAAAAAKB8TKP9hQsXLmjAgAFKTk5W3bp19eWXXyoyMlKSlJmZqfDwcBmGccP+5Z1T0ZjluXTpkuLj4+Xj4yOLxSLDMFRQUKAJEyboP//5j957770y55eWlspisWjPnj3q3bu3fH19VVhYKKvVqr59++rNN9/U3//+d3l6eqply5a6fPmyfHx8lJaWJg8P/r8GAAAAAK7hltVG165dtXz58uvaly9fruzsbGVkZGjLli0KDQ11HAsNDVVOTk61r1XRmOWxWCwKCgpS/fr1NWnSJAUEBOjOO+/U2rVrlZ+fr4iICNntdtWtW1fe3t7y8fHRgQMH5O3trbCwMC1ZskSRkZGaPHmyioqKtHLlSmVlZenDDz/Uvn379OSTT6pXr14UmgAAAABcijubv3D+/Hm1atVKjRo1UqNGjcoc8/DwkN1uN3XM8vj4+OjVV19VcXGxRo4cqaFDh8rLy0uRkZGaOXOmxowZI0maO3eujhw54rjTeeTIkevG+vHHHzVhwgRFR0dr+vTpCgoK0rp167R3795qfw4AAAAAqA63ur0VFRUli8WiLVu26OWXX5bFYlFUVJRWrVoli8WiuLg4rVixQhaLRREREWX6ZmZmymKxXDfm+vXrdc8996hhw4ZauXKlo70qY1bVunXrdPz4caWmpjraMjIy1Lx58wr7NWzYUB988IHmzJmj4uJide7cWfPmzVNAQECF/YqKipSfn19mAwAAAIDqcKtic+7cucrJyVHHjh313nvvKScnR3PnzlXfvn2Vk5OjCRMmaMCAAcrJydHOnTsrHe/MmTPq37+/JkyYoNTUVK1fv95xzNkxy/PZZ59p+fLlSktLU25uriRpx44d6tChQ5nzdu3apRdeeEH//ve/NXbsWHl5eemZZ55RYmKijh07Jg8PD6Wmpur48eMVXm/mzJny9/d3bCEhIU7FDQAAAMB9uVWx6ePjI7vdLi8vL/n6+sput8vHx0d16tSR3W6Xt7e3rFar7Ha76tWrV+l4iYmJCg8P17Bhw3TPPfcoNjbWcczZMcuzcuVKPfnkk+rTp4+WLl2qs2fP6sSJE2rXrl2Z8x566CGtWrVKTz31lN555x2dOHFCrVu3VmxsrP7xj3/oyJEjslgsevDBB9WlSxeVlpaWe71JkyYpLy/PsVVWnAIAAADAr/HMZg1kZ2eXWfCnWbNmLrnO+fPnVa9ePY0aNUqdOnXS+fPn1a9fP3l6elbYLzg4WC+88IKio6PVr18/R3uHDh20bNmyGy4SZLPZZLPZTP0MAAAAANyLWxabHh4eFb7CpKqCgoJ06tQpx35WVlaNxywsLNT+/fu1Z88eSVK7du1UWFiorVu3qmnTpurWrZtmzZqlzMzM6/rm5eVp9+7dOnv2rA4cOCBJ6tixowoLC3X69GlJUmpqqiZMmKC77rqrxrECAAAAwI241TTaa5o1a6bk5GRlZ2crKSlJJSUlTo3TvXt3paena8WKFcrIyCgzjdZZu3bt0qOPPqrExEQtXbpUX3zxhQ4dOqSgoCBt2rRJiYmJatOmjcaPH69Lly45+hUUFCgvL085OTnq3Lmz0tPTdfny5XIXNSqvDQAAAADM5JZ3NqdMmaIBAwYoLCxMoaGhOnjwYKVTUssTHByshIQEjRs3TgUFBXrxxReVkpJSo9g6duyoM2fOyMfHx9F24sQJzZgxQ19++aXWrVunyMhIDR06VK1atdI777yjPn36qKSkRF27dtX06dMlSXv27NGJEydkGIbOnj3reG1LSUmJ2rZtW6MYAQAAAKAyFsOM+aRwmezsbLVo0ULPPfec3nrrrTKvLVm4cKGWLFmizZs3q0GDBuX2P3HihB566KEy02hHjx6tHTt2VDmG/Pz8q6vSRq+Wh823zLHM+B5OfCoAAAAAt6NrtUFeXp78/PwqPJdi8ya4dpfx11q0aFHundH8/PwbJrK0tPSGC/1IkmEYKigokK+v7w3PqQzFJgAAAACpesWmW06jvdmuLf7za1artdz2ipJYUaEpXX0+syaF5i/ti3ui0i8UAAAAAEgUmzdF06ZNb3YIAAAAAOBSbrkaLQAAAADAtSg2AQAAAACmo9gEAAAAAJiOYhMAAAAAYDqKTQAAAACA6Sg2AQAAAACmo9gEAAAAAJiOYhMAAAAAYDqKTQAAAACA6Sg2AQAAAACmo9gEAAAAAJiOYhMAAAAAYDqKTQAAAACA6bxudgC4fbSM2SgPm2+Ztsz4HjcpGgAAAAC3Mu5sAgAAAABMR7F5i9u0aZP279/vdP+ioiITowEAAACAqqHYvIUVFhZqxIgR+uKLL8o9XlxcLMMwbth/06ZNuv/++3X69GlXhQgAAAAA5aLY/IULFy6oZ8+e8vX1VVBQkHbu3Ok4lpmZKYvFUmH/8s6paMzKvP766/rf//6n6dOny263l9l8fX1ls9l06NChcvuWlpZq3LhxioiI0F133VXlawIAAACAGdxygaCuXbtq8ODBGjx4cJn25cuXKzs7WxkZGcrNzVVAQIDjWGhoqHJycqp9rYrGrMiMGTO0YcMG9ezZU926dVN0dHS1rhsXF6cjR45o3bp1kqS0tDQ9+OCD1Q0fAAAAAJzCnc1fOH/+vFq1aqVGjRrp/vvv15133uk45uHhIbvdbuqYNzJ58mStXLlSycnJatKkiWbNmqU2bdo4tpYtWyosLEyfffZZuf2TkpI0Y8YMLVu2TKGhoUpNTVW7du20fv36ascPAAAAAM6wGBU99PcbExUVpSVLlpRpGzFihLp27aoBAwaUaW/evLnS09Md+5mZmQoPD7/uGcn169crOjpaubm5Gj16tGJiYmQYhlatWlXpmDdy+vRp1alTRw0aNFBUVJQiIiKqfGdz79696tKli6KjoxUTE6Pi4mK1b99ewcHB+vzzz6s0RlFRUZmFhfLz8xUSEqKQ6NW8+gQAAABwY/n5+fL391deXp78/PwqPNetptHOnTtX8fHx6tmzpwYOHKiBAwfKZrPJy8tLOTk5io+PV1ZWlhYtWiRPT89Kxztz5oz69++vefPm6dFHH9XAgQMdx/r27evUmJLKPGNZWlqqadOmad68eY42wzBUWFio0NDQMs+ApqamqlevXnr55ZcVExMjSXr77beVk5OjpKSkKl1bkmbOnKm4uLgqnw8AAAAAv+ZW02h9fHxkt9vl5eUlX19f2e12+fj4qE6dOrLb7fL29pbVapXdble9evUqHS8xMVHh4eEaNmyY7rnnHsXGxjqOOTvmrxUWFmrq1KnKzMx0bMeOHdOZM2fKFJrp6enq2rWrRo0apTlz5kiSUlJSNGvWLK1bt07169dXbm6uSkpKKr3mpEmTlJeX59iOHz9e7bgBAAAAuDe3urNptuzsbIWGhjr2mzVrZtrYhmHIYrEoNjZWdevWVXJyss6cOeOYmltQUCBvb2/H6rcRERHavn27YxGgzMxM9e/fXwkJCWrTpo2kq3dbu3TpoqlTp1Z4bZvNJpvNZtpnAQAAAOB+3OrO5jUeHh4Vvp+yqoKCgnTq1CnHflZWVo3HlK4+M9mqVStlZmZq1qxZ2rp1q86dO6eoqCidPHlSkjRq1KjrisZrheapU6f01FNPKT4+Xk8//bTj+MSJEzV9+nTt2rXLlDgBAAAA4Ebcsths1qyZkpOTlZ2draSkpCpNLS1P9+7dlZ6erhUrVigjI6PMNNqaWLdunYqLixUWFqb09HTl5eWpX79+Gj58uGOBoXHjxmnRokVKSEgo03fv3r3q3LmzJkyYoEGDBkmSLl26pOzsbIWEhKht27Z6+eWXVVxcbEqsAAAAAFAetyw2p0yZooyMDIWFhSkqKkqlpaVOjRMcHKyEhATFxcWpU6dO6tixoynxvf322xo3bpwsFos8PT118eJFSdKsWbPUrVs3paamatSoUVq9erUWLFjgKJa//fZbPfTQQzp16pTi4uLUoEED1alTR/7+/mrTpo169eqlK1euKCMjQ/PnzzclVgAAAAAoj1u9+uR2UFhYqOnTpysmJkZ16tTRa6+9poULF5ZZXMhisWjy5MkaO3as49lO6er029jYWN1///0KDQ1Vo0aNFBgYqPr16zvOkaRp06Zp27Zt+uqrr6oU07XljXn1CQAAAODeqvPqE4rNm8But5fb3qJFC6WkpLj8+kVFRfLy8qryq1goNgEAAABIvGfzlrdnz55y261Wa61c39mVZvfFPVHpFwoAAAAAJIrNm6Jp06Y3OwQAAAAAcCm3XCAIAAAAAOBaFJsAAAAAANNRbAIAAAAATEexCQAAAAAwHcUmAAAAAMB0FJsAAAAAANNRbAIAAAAATEexCQAAAAAwHcUmAAAAAMB0FJsAAAAAANNRbAIAAAAATEexCQAAAAAwHcUmAAAAAMB0Xjc7ANw+WsZslIfNt0xbZnyPmxQNAAAAgFsZdzYBAAAAAKaj2LxFGYZxXVtiYqK+++67SvulpaUpLi5OBQUFrgoPAAAAACpEsXkLWrVqlTp37qwjR46UaT979qyGDx+ukpKS6/qcO3dOkZGRstvteuSRR3T06FF9//33mjJliry9vWW32x2b1WrV2LFja+vjAAAAAHBDFJu/cOHCBfXs2VO+vr4KCgrSzp07HccyMzNlsVgq7F/eORWNeSPPPvusWrVqpW7dumn8+PHy8/NTaGioJk6cqPT0dIWHh6tp06Zq3LixWrRoIUlq2LCh/va3v2nv3r1q0KCBli9frg4dOsjHx0cTJ05Ubm6uY+vXr5+8vb2d+BcCAAAAgKpxywWCunbtqsGDB2vw4MFl2pcvX67s7GxlZGQoNzdXAQEBjmOhoaHKycmp9rUqGvNGvL29tWjRIh09elRNmjRRfHy8UlJS9NJLL+mHH36Qt7e3SkpK5OnpWaZfRESETp8+XaattLRUFy9eLNNeWFhYaeEMAAAAADXhlsXmjZw/f16tWrVSo0aN1KhRozLHPDw8ZLfbTR3zRtasWaM+ffooPDxcklRSUqI//elPio2Nlbe3t+bMmaPDhw9r8eLFjj779+/XoEGDJF2dbtumTRsNGTJE9evX19q1a5WUlFTmGh07dqz2ZwEAAACAqrIY5a1E8xsVFRWlJUuWlGkbMWKEunbtqgEDBpRpb968udLT0x37mZmZCg8Pv27hnvXr1ys6Olq5ubkaPXq0YmJiZBiGVq1aVemY5Tl37pxatmyp++67Tx9//LGCg4M1ZswY5efna9myZbp8+bKOHj2qzp07a/z48Xr99dclSZcvX9b58+e1bt06zZgxQ7t375avr6/8/f2r/e9UVFSkoqIix35+fr5CQkIUEr2aV58AAAAAbiw/P1/+/v7Ky8uTn59fhee6VbFZUFCgoqIi9ezZUwMHDtTAgQNls9nk5eWln3/+WfHx8crKytKiRYvk6empevXqOfqWV2yeOXNGd999t+bNm6dHH31UAwcO1M6dO2UYhq5cuVLpmDeSl5enYcOGKTIyUg8++KAef/xxBQUFyd/fX3a7XQ0aNFBgYKA2bNigTz75RI8//rij79NPP629e/dqypQpGjhwoLp06aLTp0/LarWqoKBAvr6+KiwsVEREhDZv3lzu9WNjYxUXF3ddO8UmAAAA4N6qU2y61TRaHx8f+fj4yMvLS76+vmWmxdrtdnl7e8tqtVZ5umxiYqLCw8M1bNgwSVeLtB49rhZfderUcWpMSfL399fq1at17NgxhYWF6ZtvvtHZs2cVEhKiY8eO6bHHHtPSpUs1fvx4BQcHO/rt2bNH33//vSwWi1JTU3X8+HGlpaVJulosd+jQQZmZmZVef9KkSRozZoxj/9qdTQAAAACoKlajrYHs7GyFhoY69ps1a2ba2N9++63atWunoqIiHThwQJ9++qn27t2rjRs36sKFC1q6dKlatmzpKGILCwv10ksv6Y033pAkTZw4UVu3blVxcbFKS0vLjF1aWlru61Ousdls8vPzK7MBAAAAQHW4ZbHp4eFx3bOXzggKCtKpU6cc+1lZWTUe85pZs2Zp6NChstlsKiwsVJMmTWSxWGSxWOTp6Skvr7I3pd9//31ZrVb94Q9/kHR1ZdqkpCTHokJt27bV2bNn1bBhQ9WrV0/Lly83LVYAAAAA+DW3LDabNWum5ORkZWdnKykpqcK7fBXp3r270tPTtWLFCmVkZCg2NtaU+Pbt26evvvpKY8eOlSTt3LlTrVu3LvfcS5cuSZKGDx+uDz74QIZhOAppq9WqmJgYXb58Wd99952CgoJ07tw5/fzzzxo6dKgpsQIAAABAedyy2JwyZYoyMjIUFhamqKio66aZVlVwcLASEhIUFxenTp06mfI6kZKSEkVFRWnIkCEKDAzUzp07lZiYqB49eqi0tFSGYchisThWi33++ef1xRdf6I477lDbtm3LTJEtLi6+7g7oNVeuXHH6cwMAAABAZdxqgaBrwsLClJKScl17RXcmmzZtWu7U2759+6pv376O/bfffrvKY5bn559/VkREhOOZy2eeeUYLFixQYGCgioqKVFhYqMDAQFksFvn7+6t+/fpq3769o/+VK1d05coVSdJbb72l6dOny2q1ymKxqKSkRHa7XSUlJbp8+bI2bNigbt26VSs+AAAAAKgKt3r1ya3iRivTtmjRokwRXFxcrLS0NEVGRtZSZOW7trwxrz4BAAAA3Bvv2bzF3ej1I1arVY0bN67dYKqgOl8oAAAAAL9dvGfzFte0adObHQIAAAAAuJRbLhAEAAAAAHAtik0AAAAAgOkoNgEAAAAApqPYBAAAAACYjgWCUKlrCxbn5+ff5EgAAAAA3EzXaoKqvNSEYhOVOn/+vCQpJCTkJkcCAAAA4FZw4cIF+fv7V3gOxSYqFRAQIEnKysqq9AuF35b8/HyFhITo+PHjvGPVjZB390Xu3Re5d0/k3X3VJPeGYejChQtq3LhxpedSbKJSHh5XH+319/fnD5Gb8vPzI/duiLy7L3Lvvsi9eyLv7svZ3Ff1BhQLBAEAAAAATEexCQAAAAAwHcUmKmWz2RQTEyObzXazQ0EtI/fuiby7L3Lvvsi9eyLv7qu2cm8xqrJmLQAAAAAA1cCdTQAAAACA6Sg2AQAAAACmo9gEAAAAAJiOYhMAAFQoKytLu3bt0uXLl292KACA2wjFJrRv3z5FRkaqfv36GjdunKqyZtSaNWsUFhamxo0b65NPPqmFKOEKzuReklJSUtS8eXMXRwdXcib3cXFxCggIkM1mU58+fXThwoVaiBRmcibvY8aMUdu2bTVw4ECFh4crPT29FiKF2Zz9ey9Jubm5atSokTIzM10XIFzCmby3bt1aFovFsb3yyiu1ECnM5uxvvrS0VI888ohmz55tShwUm26uqKhIvXr1Urt27bRr1y4dOHBAy5cvr7DPvn37NGjQIP35z3/Wxo0bNXXqVB06dKh2AoZpnMm9JO3evVt9+vRRUVGR64OESziT+4SEBCUkJCgxMVH79+/XwYMHFR8fXzsBwxTO5H3z5s1av369fvjhBx0+fFjdu3cn77chZ//eXzNu3DidPn3adQHCJZzJ+6VLl5SRkaGzZ88qJydHOTk5WrBgQe0EDNPU5De/ePFi5eXlafTo0eYEY8Ctffrpp0b9+vWNn3/+2TAMw9izZ4/RsWPHCvu89tprxhNPPOHYnzdvnjF58mSXxgnzOZP7ixcvGqGhoca0adOMsLCwWogSruBM7mfOnGmkpKQ49qdOnWo89dRTLo0T5nIm7ykpKcbmzZsd+/Pnzzd69uzp0jhhPmdyf82WLVuMoKAgo0GDBsbRo0ddGCXM5kzet23bZnTo0KE2woMLOfubP3nypOHv72988803psXCnU039/3336tDhw7y9fWVdHXqxIEDByrt8/vf/96x/7vf/U67d+92aZwwnzO5r1OnjlJSUvR///d/tREiXMSZ3E+cOFEPP/ywY//QoUO69957XRonzOVM3h9++GF16dJFknTu3Dl9+OGH6tOnj8tjhbmcyb109e7IiBEj9O6776pu3bquDhMmcybvO3bs0IkTJxQYGCi73a6RI0cyk+k25OxvPjo6WmFhYTp+/LhSUlJMiYVi083l5+crPDzcsW+xWOTp6amcnJwq9/Hz89OpU6dcGifM50zurVarmjRpUhvhwYWcyf0vHT58WJ9++qmGDx/uqhDhAjXJ+9KlSxUaGqq77rpLQ4YMcWWYcAFnc//mm2/qvvvuU//+/V0dIlzAmbwfOnRInTp10rZt27Rx40Z9/fXXmjt3bm2ECxM5k/vt27frn//8p4KDg5WRkaE//vGPevXVV2scC8Wmm/Py8pLNZivT5u3trUuXLlW5T2Xn49bkTO7x21CT3JeWlmrIkCF65ZVX9MADD7gqRLhATfL+0ksvafXq1dq/f78WLlzoqhDhIs7k/uDBg1q8eLHef/99V4cHF3Em74sXL9Ynn3yi5s2bq3379po6darWrFnj6lBhMmdyv3TpUrVv317r16/XtGnTlJycrEWLFtV4XRaKTTcXEBCgH3/8sUzbhQsXZLVaq9ynsvNxa3Im9/htqEnu//KXv+inn37SrFmzXBUeXKQmebfZbOrZs6emTZumv/71r64KES5S3dwbhqHhw4dr+vTpaty4cW2ECBcw47/zQUFBOnnypNmhwcWcyf2JEyf09NNPy2KxSJJCQkIUGBiojIyMGsVCsenmIiMjtX37dsf+0aNHVVRUpICAgCr3SUtLY2rlbciZ3OO3wdnc/+tf/9KcOXO0du1ax3MguH04k/f58+fr448/duxbrVZ5enq6NE6Yr7q5z8rK0rZt2zRu3DjZ7XbZ7XZlZWWpdevWZb4PuLU585t/+OGHdfz4ccf+9u3bFRYW5tI4YT5nch8cHKyCggLH/sWLF/XTTz/V+H/jU2y6uc6dOys/P18fffSRpKvPZzz22GPy9PRUbm6uSkpKruvTt29frVq1Sv/973918eJFvfvuu3riiSdqO3TUkDO5x2+DM7k/ePCgBgwYoAULFigkJEQXL15kyvVtxpm833333YqOjtamTZt06NAhzZo1S88//3xth44aqm7umzRpoqNHj2rPnj2OrXHjxtqwYYN69+59Mz4CnODMb/6BBx7QiBEj9O2332rFihWaPXu2Ro4cWduho4acyf2AAQO0dOlSffPNNzp27JhGjRqliIgItW7dumbBmLauLW5bn3/+ueHr62s0aNDACAwMNPbv328YhmFIMtLS0srt88YbbxhWq9Xw8/Mz2rVrZ1y6dKkWI4ZZnMm9YRjGpk2bePXJba66uY+OjjYkldn4Dtx+nPnNz54922jUqJHRsGFDY+LEiUZJSUktRgyzOPv3/pqwsDBefXIbqm7ec3JyjGeffdbw8fExwsLCjEWLFtVyxDCLM7/5ZcuWGffee6/h7e1tdOjQwUhPT69xHJb/f1G4udOnT2v37t3q0KGDGjRoUKU+Bw4c0MmTJ9WlSxee87uNOZN7/DaQe/dE3t0XuXdP5N193Qq5p9gEAAAAAJiOZzYBAAAAAKaj2AQAAAAAmI5iEwAAAABgOopNAAAAAIDpKDYBAAAAAKaj2AQAAAAAmI5iEwAAAABgOopNAAAAAIDpKDYBAAAAAKb7f1gSnYrk/Xx0AAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 1000x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "回归模型RMSE: 0.8820 (对数尺度)\n"
     ]
    }
   ],
   "source": [
    "X = features.fillna(features.mean())\n",
    "y = df['is_popular']\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n",
    "\n",
    "# 5.2 热门视频分类模型\n",
    "clf = RandomForestClassifier(n_estimators=100, random_state=42)\n",
    "clf.fit(X_train, y_train)\n",
    "\n",
    "# 评估\n",
    "y_pred = clf.predict(X_test)\n",
    "print(\"\\n分类模型评估报告:\")\n",
    "print(classification_report(y_test, y_pred))\n",
    "\n",
    "# 特征重要性\n",
    "plt.figure(figsize=(10, 8))\n",
    "pd.Series(clf.feature_importances_, index=X.columns).sort_values().tail(20).plot.barh()\n",
    "plt.title('特征重要性(top 20)')\n",
    "plt.show()\n",
    "\n",
    "# 5.3 播放量回归预测\n",
    "# 只选择播放量适中的样本(去除极端值)\n",
    "reg_df = df[(df['play'] > 1000) & (df['play'] < 1e7)].copy()\n",
    "X_reg = features.loc[reg_df.index].fillna(features.mean())\n",
    "y_reg = np.log1p(reg_df['play'])  # 对数变换\n",
    "\n",
    "X_train_reg, X_test_reg, y_train_reg, y_test_reg = train_test_split(\n",
    "    X_reg, y_reg, test_size=0.2, random_state=42)\n",
    "\n",
    "reg = RandomForestRegressor(n_estimators=100, random_state=42)\n",
    "reg.fit(X_train_reg, y_train_reg)\n",
    "\n",
    "y_pred_reg = reg.predict(X_test_reg)\n",
    "rmse = np.sqrt(mean_squared_error(y_test_reg, y_pred_reg))\n",
    "print(f\"\\n回归模型RMSE: {rmse:.4f} (对数尺度)\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "319b6e99-81eb-4b59-9809-72d5412c3d6a",
   "metadata": {},
   "source": [
    "## 六. 拓展性高级分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "aace2655-a361-4a3c-9f7a-48b761f5eddb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "主题建模结果:\n",
      "主题1: saber 今日 终结 命运 quot 版本 如果 爱莉 米哈 角色\n",
      "主题2: 乐土 海瑟音 pv 角色 版本 攻略 就是 赫丽娅 星穹 铁道\n",
      "主题3: 刻律 活动 剧情 法罗斯 第二部 流程 这个 不朽 主线 33\n",
      "主题4: boss 毕业 舰长 星铁 科拉 动画短片 一个 34 什么 剧情\n",
      "主题5: 星铁 联动 米哈 这么 没有 真的 我们 玩家 游戏 崩铁\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "lda = LatentDirichletAllocation(n_components=5, random_state=42)\n",
    "lda.fit(title_tfidf)\n",
    "\n",
    "print(\"\\n主题建模结果:\")\n",
    "for i, topic in enumerate(lda.components_):\n",
    "    print(f\"主题{i+1}:\", \" \".join([tfidf.get_feature_names_out()[i] \n",
    "                               for i in topic.argsort()[-10:]]))\n",
    "\n",
    "# 6.2 UP主聚类分析\n",
    "up_features = df.groupby('up主').agg({\n",
    "    'play': ['mean', 'count'],\n",
    "    'duration_min': 'mean'\n",
    "}).droplevel(0, axis=1)\n",
    "up_features.columns = ['avg_play', 'video_count', 'avg_duration']\n",
    "\n",
    "# Handle missing values\n",
    "up_features = up_features.dropna()  # or use imputation as shown above\n",
    "\n",
    "# 标准化\n",
    "scaler = StandardScaler()\n",
    "up_scaled = scaler.fit_transform(up_features)\n",
    "\n",
    "# K-means聚类\n",
    "kmeans = KMeans(n_clusters=3, random_state=42)\n",
    "up_features['cluster'] = kmeans.fit_predict(up_scaled)\n",
    "\n",
    "plt.figure(figsize=(10, 6))\n",
    "sns.scatterplot(x='avg_play', y='video_count', hue='cluster', \n",
    "                data=up_features, palette='viridis', s=100)\n",
    "plt.title('UP主聚类分析')\n",
    "plt.xlabel('平均播放量')\n",
    "plt.ylabel('视频数量')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cc7e11f4-e2f0-4d67-a234-63a842d787b9",
   "metadata": {},
   "source": [
    "## 七. 分析结论与建议"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "55afb1d8-1ae1-4803-97b4-67cd442da098",
   "metadata": {},
   "source": [
    "### 分析结论:\n",
    "#### 1. 视频播放量呈现长尾分布，少数视频获得极高播放量\n",
    "#### 2. '攻略'和'剧情'类视频占比最高，且播放量表现较好\n",
    "#### 3. UP主的历史表现(平均播放量)是新视频表现的重要预测因素\n",
    "#### 4. 标题中的特定关键词(如'动画'、'主线'等)与播放量正相关"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f14f84c0-f1f8-4ac4-b9b5-06e98171aabb",
   "metadata": {},
   "source": [
    "### 运营建议:\n",
    "#### 1. 鼓励制作高质量的攻略和剧情解析类内容\n",
    "#### 2. 关注标题优化，包含热门关键词\n",
    "#### 3. 与高影响力UP主合作提升内容传播效果\n",
    "#### 4. 视频时长建议控制在10-30分钟之间"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bd0bf62e-2296-4a2f-bbfe-c24e6a8b6679",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
